{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook implements an efficient version of pseudobulk nb-glm based differential expression analysis with DESeq2. Pseudobulk means that all reads from a single batch group (e.g. donor) get pooled into a single observation. \n",
    "\n",
    "In general, pseudobulk is statistically preferable to but much slower than Wilcoxon, especially when you need to consider covariates. A more robust but considerably slower alternative to pseudobulk is including donors as random effects. Random effects are preferable for small cell count groups but likely give similar results to pseudobulk estimates for large groups. \n",
    "\n",
    "This idea is not at all new. The earliest reference I know for is from Lun et al: \n",
    "https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0947-7. \n",
    "\n",
    "\n",
    "A few implementation notes: \n",
    "\n",
    "1) To find markers most upregulated in a cluster, I divide samples into those in and out of the cluster. An alternative is to let each out group remain an independent pseudobulk sample. This is in fact the recommended way from Mike Love: https://support.bioconductor.org/p/118090/. While this is certainly faster than re-estimate size factors for each cluster-specific analysis, I find it gives strange results. Namely, I get more inflated p-values and significant p-values for the wrong canonical marker genes (e.g. CD14 for B cells).  \n",
    "\n",
    "2) On my laptop, it takes ~20 seconds to run do ~3000 genes from 2700 cells, 3 donors, 2 batches, and 9 cell types. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load some data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading presto\n"
     ]
    }
   ],
   "source": [
    "devtools::load_all('..')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "suppressPackageStartupMessages({\n",
    "    library(tidyverse)\n",
    "#     library(presto)\n",
    "    library(singlecellmethods)\n",
    "    library(SeuratData)\n",
    "    library(Seurat)\n",
    "    library(DESeq2)    \n",
    "})\n",
    "\n",
    "fig.size <- function (h, w) \n",
    "{\n",
    "    options(repr.plot.height = h, repr.plot.width = w)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load small dataset for exposition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "if (!SeuratData::AvailableData()['pbmc3k.SeuratData', 'Installed']) {\n",
    "    SeuratData::InstallData(\"pbmc3k\")\n",
    "}\n",
    "data(\"pbmc3k\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add fake donor and batch columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pbmc3k@meta.data$donor <- factor(sample(LETTERS[1:3], ncol(pbmc3k), TRUE))\n",
    "pbmc3k@meta.data$batch <- factor(sample(LETTERS[1:2], ncol(pbmc3k), TRUE))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 6</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>orig.ident</th><th scope=col>nCount_RNA</th><th scope=col>nFeature_RNA</th><th scope=col>seurat_annotations</th><th scope=col>donor</th><th scope=col>batch</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>AAACATACAACCAC</th><td>pbmc3k</td><td>2419</td><td> 779</td><td>Memory CD4 T</td><td>B</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>AAACATTGAGCTAC</th><td>pbmc3k</td><td>4903</td><td>1352</td><td>B           </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>AAACATTGATCAGC</th><td>pbmc3k</td><td>3147</td><td>1129</td><td>Memory CD4 T</td><td>B</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>AAACCGTGCTTCCG</th><td>pbmc3k</td><td>2639</td><td> 960</td><td>CD14+ Mono  </td><td>A</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>AAACCGTGTATGCG</th><td>pbmc3k</td><td> 980</td><td> 521</td><td>NK          </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>AAACGCACTGGTAC</th><td>pbmc3k</td><td>2163</td><td> 781</td><td>Memory CD4 T</td><td>A</td><td>A</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 6\n",
       "\\begin{tabular}{r|llllll}\n",
       "  & orig.ident & nCount\\_RNA & nFeature\\_RNA & seurat\\_annotations & donor & batch\\\\\n",
       "  & <fct> & <dbl> & <int> & <fct> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\tAAACATACAACCAC & pbmc3k & 2419 &  779 & Memory CD4 T & B & B\\\\\n",
       "\tAAACATTGAGCTAC & pbmc3k & 4903 & 1352 & B            & C & B\\\\\n",
       "\tAAACATTGATCAGC & pbmc3k & 3147 & 1129 & Memory CD4 T & B & A\\\\\n",
       "\tAAACCGTGCTTCCG & pbmc3k & 2639 &  960 & CD14+ Mono   & A & A\\\\\n",
       "\tAAACCGTGTATGCG & pbmc3k &  980 &  521 & NK           & C & B\\\\\n",
       "\tAAACGCACTGGTAC & pbmc3k & 2163 &  781 & Memory CD4 T & A & A\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 6\n",
       "\n",
       "| <!--/--> | orig.ident &lt;fct&gt; | nCount_RNA &lt;dbl&gt; | nFeature_RNA &lt;int&gt; | seurat_annotations &lt;fct&gt; | donor &lt;fct&gt; | batch &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| AAACATACAACCAC | pbmc3k | 2419 |  779 | Memory CD4 T | B | B |\n",
       "| AAACATTGAGCTAC | pbmc3k | 4903 | 1352 | B            | C | B |\n",
       "| AAACATTGATCAGC | pbmc3k | 3147 | 1129 | Memory CD4 T | B | A |\n",
       "| AAACCGTGCTTCCG | pbmc3k | 2639 |  960 | CD14+ Mono   | A | A |\n",
       "| AAACCGTGTATGCG | pbmc3k |  980 |  521 | NK           | C | B |\n",
       "| AAACGCACTGGTAC | pbmc3k | 2163 |  781 | Memory CD4 T | A | A |\n",
       "\n"
      ],
      "text/plain": [
       "               orig.ident nCount_RNA nFeature_RNA seurat_annotations donor\n",
       "AAACATACAACCAC pbmc3k     2419        779         Memory CD4 T       B    \n",
       "AAACATTGAGCTAC pbmc3k     4903       1352         B                  C    \n",
       "AAACATTGATCAGC pbmc3k     3147       1129         Memory CD4 T       B    \n",
       "AAACCGTGCTTCCG pbmc3k     2639        960         CD14+ Mono         A    \n",
       "AAACCGTGTATGCG pbmc3k      980        521         NK                 C    \n",
       "AAACGCACTGGTAC pbmc3k     2163        781         Memory CD4 T       A    \n",
       "               batch\n",
       "AAACATACAACCAC B    \n",
       "AAACATTGAGCTAC B    \n",
       "AAACATTGATCAGC A    \n",
       "AAACCGTGCTTCCG A    \n",
       "AAACCGTGTATGCG B    \n",
       "AAACGCACTGGTAC A    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(pbmc3k@meta.data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Collapse to pseudobulk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>seurat_annotations</th><th scope=col>donor</th><th scope=col>batch</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>sample_37</th><td>Memory CD4 T</td><td>B</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_48</th><td>B           </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_10</th><td>Memory CD4 T</td><td>B</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>sample_2</th><td>CD14+ Mono  </td><td>A</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>sample_51</th><td>NK          </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_1</th><td>Memory CD4 T</td><td>A</td><td>A</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 3\n",
       "\\begin{tabular}{r|lll}\n",
       "  & seurat\\_annotations & donor & batch\\\\\n",
       "  & <fct> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\tsample\\_37 & Memory CD4 T & B & B\\\\\n",
       "\tsample\\_48 & B            & C & B\\\\\n",
       "\tsample\\_10 & Memory CD4 T & B & A\\\\\n",
       "\tsample\\_2 & CD14+ Mono   & A & A\\\\\n",
       "\tsample\\_51 & NK           & C & B\\\\\n",
       "\tsample\\_1 & Memory CD4 T & A & A\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 3\n",
       "\n",
       "| <!--/--> | seurat_annotations &lt;fct&gt; | donor &lt;fct&gt; | batch &lt;fct&gt; |\n",
       "|---|---|---|---|\n",
       "| sample_37 | Memory CD4 T | B | B |\n",
       "| sample_48 | B            | C | B |\n",
       "| sample_10 | Memory CD4 T | B | A |\n",
       "| sample_2 | CD14+ Mono   | A | A |\n",
       "| sample_51 | NK           | C | B |\n",
       "| sample_1 | Memory CD4 T | A | A |\n",
       "\n"
      ],
      "text/plain": [
       "          seurat_annotations donor batch\n",
       "sample_37 Memory CD4 T       B     B    \n",
       "sample_48 B                  C     B    \n",
       "sample_10 Memory CD4 T       B     A    \n",
       "sample_2  CD14+ Mono         A     A    \n",
       "sample_51 NK                 C     B    \n",
       "sample_1  Memory CD4 T       A     A    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_collapsed <- collapse_counts(pbmc3k@assays$RNA@counts, \n",
    "                                  pbmc3k@meta.data, \n",
    "                                  c('seurat_annotations', 'donor', 'batch'))\n",
    "head(data_collapsed$meta_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Do DESeq2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: meta_data should only contain pseudobulk identifying variables\n",
      "Filtered out 10729 genes, analyzing 2985 genes\n",
      "All vars: seurat_annotations, donor, batch\n",
      "Contrast var: seurat_annotations\n",
      "Memory CD4 T\n",
      "B\n",
      "CD14+ Mono\n",
      "NK\n",
      "CD8 T\n",
      "Naive CD4 T\n",
      "FCGR3A+ Mono\n",
      "DC\n",
      "Platelet\n"
     ]
    }
   ],
   "source": [
    "res_mat <- pseudobulk_deseq2(~seurat_annotations + donor + batch, \n",
    "                             data_collapsed$meta_data,\n",
    "                             data_collapsed$counts_mat, verbose = TRUE)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>group</th><th scope=col>feature</th><th scope=col>baseMean</th><th scope=col>log2FoldChange</th><th scope=col>lfcSE</th><th scope=col>stat</th><th scope=col>pvalue</th><th scope=col>padj</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>B</td><td>CD79B</td><td> 312.8710</td><td>4.596606</td><td>0.11896885</td><td>38.63706</td><td> 0.000000e+00</td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>B</td><td>MS4A1</td><td> 195.0316</td><td>5.820981</td><td>0.16796181</td><td>34.65658</td><td>3.555957e-263</td><td>5.307266e-260</td></tr>\n",
       "\t<tr><td>B</td><td>CD74 </td><td>2687.7845</td><td>2.712676</td><td>0.08270321</td><td>32.80013</td><td>5.863802e-236</td><td>5.834483e-233</td></tr>\n",
       "\t<tr><td>B</td><td>CD79A</td><td> 379.9878</td><td>6.989701</td><td>0.22135839</td><td>31.57640</td><td>7.786960e-219</td><td>5.811019e-216</td></tr>\n",
       "\t<tr><td>B</td><td>CD37 </td><td> 589.0086</td><td>2.081310</td><td>0.07125680</td><td>29.20859</td><td>1.508602e-187</td><td>9.006352e-185</td></tr>\n",
       "\t<tr><td>B</td><td>TCL1A</td><td> 176.3964</td><td>6.614657</td><td>0.22864700</td><td>28.92956</td><td>5.073640e-184</td><td>2.524136e-181</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       " group & feature & baseMean & log2FoldChange & lfcSE & stat & pvalue & padj\\\\\n",
       " <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t B & CD79B &  312.8710 & 4.596606 & 0.11896885 & 38.63706 &  0.000000e+00 &  0.000000e+00\\\\\n",
       "\t B & MS4A1 &  195.0316 & 5.820981 & 0.16796181 & 34.65658 & 3.555957e-263 & 5.307266e-260\\\\\n",
       "\t B & CD74  & 2687.7845 & 2.712676 & 0.08270321 & 32.80013 & 5.863802e-236 & 5.834483e-233\\\\\n",
       "\t B & CD79A &  379.9878 & 6.989701 & 0.22135839 & 31.57640 & 7.786960e-219 & 5.811019e-216\\\\\n",
       "\t B & CD37  &  589.0086 & 2.081310 & 0.07125680 & 29.20859 & 1.508602e-187 & 9.006352e-185\\\\\n",
       "\t B & TCL1A &  176.3964 & 6.614657 & 0.22864700 & 28.92956 & 5.073640e-184 & 2.524136e-181\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| group &lt;chr&gt; | feature &lt;chr&gt; | baseMean &lt;dbl&gt; | log2FoldChange &lt;dbl&gt; | lfcSE &lt;dbl&gt; | stat &lt;dbl&gt; | pvalue &lt;dbl&gt; | padj &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| B | CD79B |  312.8710 | 4.596606 | 0.11896885 | 38.63706 |  0.000000e+00 |  0.000000e+00 |\n",
       "| B | MS4A1 |  195.0316 | 5.820981 | 0.16796181 | 34.65658 | 3.555957e-263 | 5.307266e-260 |\n",
       "| B | CD74  | 2687.7845 | 2.712676 | 0.08270321 | 32.80013 | 5.863802e-236 | 5.834483e-233 |\n",
       "| B | CD79A |  379.9878 | 6.989701 | 0.22135839 | 31.57640 | 7.786960e-219 | 5.811019e-216 |\n",
       "| B | CD37  |  589.0086 | 2.081310 | 0.07125680 | 29.20859 | 1.508602e-187 | 9.006352e-185 |\n",
       "| B | TCL1A |  176.3964 | 6.614657 | 0.22864700 | 28.92956 | 5.073640e-184 | 2.524136e-181 |\n",
       "\n"
      ],
      "text/plain": [
       "  group feature baseMean  log2FoldChange lfcSE      stat     pvalue       \n",
       "1 B     CD79B    312.8710 4.596606       0.11896885 38.63706  0.000000e+00\n",
       "2 B     MS4A1    195.0316 5.820981       0.16796181 34.65658 3.555957e-263\n",
       "3 B     CD74    2687.7845 2.712676       0.08270321 32.80013 5.863802e-236\n",
       "4 B     CD79A    379.9878 6.989701       0.22135839 31.57640 7.786960e-219\n",
       "5 B     CD37     589.0086 2.081310       0.07125680 29.20859 1.508602e-187\n",
       "6 B     TCL1A    176.3964 6.614657       0.22864700 28.92956 5.073640e-184\n",
       "  padj         \n",
       "1  0.000000e+00\n",
       "2 5.307266e-260\n",
       "3 5.834483e-233\n",
       "4 5.811019e-216\n",
       "5 9.006352e-185\n",
       "6 2.524136e-181"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(res_mat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A tibble: 10 × 10</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>rank</th><th scope=col>B</th><th scope=col>CD14+ Mono</th><th scope=col>CD8 T</th><th scope=col>DC</th><th scope=col>FCGR3A+ Mono</th><th scope=col>Memory CD4 T</th><th scope=col>Naive CD4 T</th><th scope=col>NK</th><th scope=col>Platelet</th></tr>\n",
       "\t<tr><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td> 1</td><td>CD79B    </td><td>S100A9</td><td>CCL5</td><td>HLA-DPB1</td><td>LST1  </td><td>LTB    </td><td>RPS27 </td><td>PRF1  </td><td>PPBP   </td></tr>\n",
       "\t<tr><td> 2</td><td>MS4A1    </td><td>S100A8</td><td>NKG7</td><td>FCER1A  </td><td>COTL1 </td><td>IL32   </td><td>RPL9  </td><td>GNLY  </td><td>PF4    </td></tr>\n",
       "\t<tr><td> 3</td><td>CD74     </td><td>FTL   </td><td>GZMH</td><td>HLA-DRB1</td><td>FTL   </td><td>LDHB   </td><td>RPS3A </td><td>NKG7  </td><td>GNG11  </td></tr>\n",
       "\t<tr><td> 4</td><td>CD79A    </td><td>LYZ   </td><td>GZMK</td><td>CLEC10A </td><td>AIF1  </td><td>IL7R   </td><td>RPS27A</td><td>GZMA  </td><td>NRGN   </td></tr>\n",
       "\t<tr><td> 5</td><td>CD37     </td><td>FTH1  </td><td>CD8A</td><td>CD74    </td><td>FCER1G</td><td>CD3D   </td><td>RPL31 </td><td>CTSW  </td><td>GPX1   </td></tr>\n",
       "\t<tr><td> 6</td><td>TCL1A    </td><td>TYROBP</td><td>GZMA</td><td>CST3    </td><td>SAT1  </td><td>CD3E   </td><td>RPS25 </td><td>FGFBP2</td><td>MPP1   </td></tr>\n",
       "\t<tr><td> 7</td><td>BANK1    </td><td>S100A6</td><td>CTSW</td><td>HLA-DRA </td><td>FCGR3A</td><td>TNFRSF4</td><td>LDHB  </td><td>SPON2 </td><td>TPM4   </td></tr>\n",
       "\t<tr><td> 8</td><td>HLA-DRA  </td><td>S100A4</td><td>CD3D</td><td>HLA-DPA1</td><td>FTH1  </td><td>AQP3   </td><td>RPS29 </td><td>CST7  </td><td>NGFRAP1</td></tr>\n",
       "\t<tr><td> 9</td><td>LINC00926</td><td>FCN1  </td><td>CST7</td><td>HLA-DRB5</td><td>IFITM3</td><td>CD2    </td><td>NPM1  </td><td>CLIC3 </td><td>CD9    </td></tr>\n",
       "\t<tr><td>10</td><td>HLA-DRB1 </td><td>LGALS2</td><td>GZMM</td><td>HLA-DQA2</td><td>PSAP  </td><td>TRAT1  </td><td>CCR7  </td><td>CCL4  </td><td>NCOA4  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 10 × 10\n",
       "\\begin{tabular}{r|llllllllll}\n",
       " rank & B & CD14+ Mono & CD8 T & DC & FCGR3A+ Mono & Memory CD4 T & Naive CD4 T & NK & Platelet\\\\\n",
       " <int> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr> & <chr>\\\\\n",
       "\\hline\n",
       "\t  1 & CD79B     & S100A9 & CCL5 & HLA-DPB1 & LST1   & LTB     & RPS27  & PRF1   & PPBP   \\\\\n",
       "\t  2 & MS4A1     & S100A8 & NKG7 & FCER1A   & COTL1  & IL32    & RPL9   & GNLY   & PF4    \\\\\n",
       "\t  3 & CD74      & FTL    & GZMH & HLA-DRB1 & FTL    & LDHB    & RPS3A  & NKG7   & GNG11  \\\\\n",
       "\t  4 & CD79A     & LYZ    & GZMK & CLEC10A  & AIF1   & IL7R    & RPS27A & GZMA   & NRGN   \\\\\n",
       "\t  5 & CD37      & FTH1   & CD8A & CD74     & FCER1G & CD3D    & RPL31  & CTSW   & GPX1   \\\\\n",
       "\t  6 & TCL1A     & TYROBP & GZMA & CST3     & SAT1   & CD3E    & RPS25  & FGFBP2 & MPP1   \\\\\n",
       "\t  7 & BANK1     & S100A6 & CTSW & HLA-DRA  & FCGR3A & TNFRSF4 & LDHB   & SPON2  & TPM4   \\\\\n",
       "\t  8 & HLA-DRA   & S100A4 & CD3D & HLA-DPA1 & FTH1   & AQP3    & RPS29  & CST7   & NGFRAP1\\\\\n",
       "\t  9 & LINC00926 & FCN1   & CST7 & HLA-DRB5 & IFITM3 & CD2     & NPM1   & CLIC3  & CD9    \\\\\n",
       "\t 10 & HLA-DRB1  & LGALS2 & GZMM & HLA-DQA2 & PSAP   & TRAT1   & CCR7   & CCL4   & NCOA4  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 10 × 10\n",
       "\n",
       "| rank &lt;int&gt; | B &lt;chr&gt; | CD14+ Mono &lt;chr&gt; | CD8 T &lt;chr&gt; | DC &lt;chr&gt; | FCGR3A+ Mono &lt;chr&gt; | Memory CD4 T &lt;chr&gt; | Naive CD4 T &lt;chr&gt; | NK &lt;chr&gt; | Platelet &lt;chr&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|\n",
       "|  1 | CD79B     | S100A9 | CCL5 | HLA-DPB1 | LST1   | LTB     | RPS27  | PRF1   | PPBP    |\n",
       "|  2 | MS4A1     | S100A8 | NKG7 | FCER1A   | COTL1  | IL32    | RPL9   | GNLY   | PF4     |\n",
       "|  3 | CD74      | FTL    | GZMH | HLA-DRB1 | FTL    | LDHB    | RPS3A  | NKG7   | GNG11   |\n",
       "|  4 | CD79A     | LYZ    | GZMK | CLEC10A  | AIF1   | IL7R    | RPS27A | GZMA   | NRGN    |\n",
       "|  5 | CD37      | FTH1   | CD8A | CD74     | FCER1G | CD3D    | RPL31  | CTSW   | GPX1    |\n",
       "|  6 | TCL1A     | TYROBP | GZMA | CST3     | SAT1   | CD3E    | RPS25  | FGFBP2 | MPP1    |\n",
       "|  7 | BANK1     | S100A6 | CTSW | HLA-DRA  | FCGR3A | TNFRSF4 | LDHB   | SPON2  | TPM4    |\n",
       "|  8 | HLA-DRA   | S100A4 | CD3D | HLA-DPA1 | FTH1   | AQP3    | RPS29  | CST7   | NGFRAP1 |\n",
       "|  9 | LINC00926 | FCN1   | CST7 | HLA-DRB5 | IFITM3 | CD2     | NPM1   | CLIC3  | CD9     |\n",
       "| 10 | HLA-DRB1  | LGALS2 | GZMM | HLA-DQA2 | PSAP   | TRAT1   | CCR7   | CCL4   | NCOA4   |\n",
       "\n"
      ],
      "text/plain": [
       "   rank B         CD14+ Mono CD8 T DC       FCGR3A+ Mono Memory CD4 T\n",
       "1   1   CD79B     S100A9     CCL5  HLA-DPB1 LST1         LTB         \n",
       "2   2   MS4A1     S100A8     NKG7  FCER1A   COTL1        IL32        \n",
       "3   3   CD74      FTL        GZMH  HLA-DRB1 FTL          LDHB        \n",
       "4   4   CD79A     LYZ        GZMK  CLEC10A  AIF1         IL7R        \n",
       "5   5   CD37      FTH1       CD8A  CD74     FCER1G       CD3D        \n",
       "6   6   TCL1A     TYROBP     GZMA  CST3     SAT1         CD3E        \n",
       "7   7   BANK1     S100A6     CTSW  HLA-DRA  FCGR3A       TNFRSF4     \n",
       "8   8   HLA-DRA   S100A4     CD3D  HLA-DPA1 FTH1         AQP3        \n",
       "9   9   LINC00926 FCN1       CST7  HLA-DRB5 IFITM3       CD2         \n",
       "10 10   HLA-DRB1  LGALS2     GZMM  HLA-DQA2 PSAP         TRAT1       \n",
       "   Naive CD4 T NK     Platelet\n",
       "1  RPS27       PRF1   PPBP    \n",
       "2  RPL9        GNLY   PF4     \n",
       "3  RPS3A       NKG7   GNG11   \n",
       "4  RPS27A      GZMA   NRGN    \n",
       "5  RPL31       CTSW   GPX1    \n",
       "6  RPS25       FGFBP2 MPP1    \n",
       "7  LDHB        SPON2  TPM4    \n",
       "8  RPS29       CST7   NGFRAP1 \n",
       "9  NPM1        CLIC3  CD9     \n",
       "10 CCR7        CCL4   NCOA4   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_markers_dds(res_mat, lfc_min = 1, padj_max = .05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Volcano plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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pahl7ASxESL6d1AaCTH3mW34RjyStL/VNf7Renu7FaTSbXITZIIoXJeOJ39demh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y0EQO0vs2xMlgHA0mKRy0oSETmrijMqRx5+Sd6U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\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vOSWvOCatMv/bP7KtjABYVe35iTZxak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nY+4ou21iJPZIOvc3r8fTN4V7dyA76cuj\nny7GVPwWCLROeTUd4xnJDACk9c1JfG/Anhbuq8GNz2fziyQZI7Qnx57ldvI9eCu/m8n+bdXa\nqLburVBD08M49q5k+q5kGgAQwElO+93hYNf3SYQSmv65UB7GMqFOpdVKzg250dstomkflcRm\nRa1j6CNs/MA+W/jDFA0YQNdQLgMAAAi6qzLhn9+pBGCJIsEEi1gq0MyEAcPO87p/53b9aU3z\nLUH/SCs3nGNdJAkAY228hyK/lySAfgN6x/NOsQQA7xZLz+UKboo8zm67Pui/yu89QRDnlMQz\ndr5q26JpXtrW8W7xZzWla+PJe6tCp7j6sBLTzsxInn8tlU7qurebHfxhSbASxCZHhi/F8tWx\nRFeOci1D3xEK9HXETtEwn8zlj3PYH6mpAoBRVu4Ul2OZqv1u1dpXkulrPTvdbdZ3tGhaNU0F\n1p+a7mO1AMBaVesyoDOGsUiSs7qxG8f2J3j0ChV3QLOqNXTTqImqmglgJdBoq+XFXP4Eh+1A\n3goAbpIAgHZNv7D3Kn1+K5Y9JHlUt2VtBDDB7Xi/WPpeko/Y5Sqz7goGNL3+/InqfG5pmu5d\nhR2SJDc+XG/tdoM9JzRtviildL2eZQAgZxj7r24e77DzJDmnJKySlSEc26yoFE13Nz7nCuJ9\n8dRiSWYRGsVbbqqtHtVttzTAxaFeECIlSfKzXOHkpSvrGfqh+pqBDL1aUafEEosk2U4SLEEM\nZJhrqwKHdT5FBsYzk2nRNOYI4hxBRACnely3h0MOiny/JAzjWGdnWSmSJBFCD2Xzd8ZTcue1\nuxWhy4L+66sC27y82hX/t4lrN2Q3WL6EalkLBAnYgE2VKTHqGshICwCwnLWlpl6SlT1aVs8N\neOpqq98TygAwxmE7aP3ENRIhjNA23ypd5Vt75WbbzsKlOxUJXX8uWwCAA3jrUJZZo2ov5Ysf\nlcSnasMAkNlslakdxeRY4r2iEKCopK6zgDgCFQzzovZY3PBf0gdFrXd+/l5T9WIydcrayNSQ\nf1+rpUPTZ6QyH5fES3webiPX8g+SfEZrm48k7w4Hh3HsWkW9P5U9N9r+Sn3N1up1SiZ+KJ39\nWBBimj6AYU51OY63236Q5XZNb6DpfXlLd8f2UllRTXzi+uVmR1i4oVbL/GIJfksGtI0gCoZp\n4vUKOlaeNRuBAMDEcF8q80A6I3UmjhzAW6aHQ4P7I6R7xu94q40gro0l3CS5SlVYhPa2WmTD\nRABFE1/l9y6WlJOaowfy1hqG/qwkAMAoC3eet9dCKBUMPLlhIJQVVeQKdkGtj13BgP4lmes+\nKrm5GVXtXtkzBrijtW1atK1srLvhGAIFaWaI1fJOoSSb5jDe+vRudVNbo8N5q7NbY25rid7S\nGg0y9OEel2riT3L5D5aseH7YkNP7QPvs5uWrfTT15d57vpbOPF0ofVssJXWdQMCT5F422+f5\nwplrI38Nh2iCqGboHwTxqXhylN32gyDUsuxw3vpmNv+dJPspullRXxo2pHuXvpLK3BJLHOVx\n3d1YP4y3rpHk65tb74knB9htF4ZD29baij1KkuQmrt0++6nvvA4Yw7pCKpswoMlIC6qqwR1t\nVKhqt4l/MVub9Ydn7K5JhMMxmqIBYHap7Lfbh1ktPEkCwLfFUkrTx7hc23yrVBpMUVSv3GyZ\nTKbnO/mVclciLWETAG4J+QcwDADML0t/aInenkwBQB9VhusJSV1/vVAM0VTGMO4NB892O0mE\nPiqJZ7W23dqRGmdou/n88BsL5xhtt70wbMhfV635Q3O0soVAcLbbeYXfO1cot+l6LU3tY7VU\njOnpyQyH0H8G1FeWufa3WsY7bIesabkzmdkqA3q5rJzaEk3qRj1Nj+QsqxT5ivb41QjpnUNE\nPUPfEw4dZrNW/jRh04tpFELGb6x66KE2/q1C6eV8YULn8o6G8ePpnJUgKn7oacn0jFRmnI0/\n3+t2kuQ8UXwgnT25JTp3UIOrP2+kB7gpcl/e+llJIADV0jQg/ElJwBgO4q1fl8tTE+nXGmuf\nz+Y/F8TvJVkxcR1Dvz+grhfT+4ZyzMcloVnVGrsNrf8VRQDYbVdcZNgVDOgN7AOapiuF1HO5\nXO96oCmKcrlcvW6OsCxbEWmv7Pn+VGZqIn2Yzfo3nydIUQsk+aaOZFRRRrD0vEENXpJM6vqN\nHfE1knx/dairMctl5bZIdA+OPczGN1LkYTZ+qs91Rmv7RauaxmDT0asRxgzHfVMsneL3HvT9\nomZVc5BE0TABAAFkNH1m0Hu2In8rSve1xbp+MoBl3q+r/nepdF0s+X4mBwDNkpwg1Onh4BEk\n6joLjuPui7bVMvRTVQFGkYuKTOnGbR7XSkGcHmk7ld1Gc4fneYvFYhhGV/2tLshEh/Vnoxn/\nkg1tFHIEgCYrhUyGTKesAIIky+n02yWRQvB0PPF0PEEjmORxj7Zyt8ZTTpL8A0dnMhnVxI9n\ncx8WhaimNzL0iU77n9zO7gPWckW9N5FeJMsYw0gLe0XAN5xj7XY7y7KaphUKhW075V8Rn5TE\nb8tlwTCHcezJLsfm62NtLR+WhAOs1m/K0jWx5OO1VS6S3NdqOYy3fiyUXST5O36nW1JcKikm\nhg5Nv9TvObeSXIvxcU3LG3WyhbW+NH/B9DWLtX0PUvc7EJO/ptG7Q9N9FElv66v6jIBvDIJ3\n8oU1ihqgyENtfIuqHbymuUPrEiaiplUFxjvs35Slw218qFs5bhdJHm+3PZHNqxgzW9aAf2Vy\nN8VTlQCzVk0TTPNEh71ZzesYn+FyXuL3/FSW7kllzo60vd9YN9LCAcAwjq1MdboXUWpSlOVl\n6W/VVdt21r9SznA5nsjkLo/F5wrlfXnOxPBsrrBMVm4LBWwEUTTMWensUXbb8/XVlYsxxsqN\nsnCntLQ9nS1ctk26hP1UWCTJn5eEQ3keEfBjWdYwHsmxGd1cKiv/CPrvTKTHNbUMZBjRxJJp\n1jP07Iba3hXHOMvlfDSTmxhpf6A6NNLCaRi/kCvMyuQOsVl3SQGWX9MQ/FtAMfA/U9mBLHOO\n2zWUY4MUNZRjR3Pc75paPigJ7xcFniBE0yQABjPMk9n8x4J4tI0/3eWckkibGJbKylJZgYqE\nasB7czh0elPLHLGnhfE2QMfYwHhOviDqxlO14bll6bls/v0BdRNa21O6Pnplc9E0WIQUjGsY\nuk3VAGCtos5KZy/1ew638V+J5SZFvSOZPsZuO2cj/Y3FonSK004j9EaheHs8HdE0ALACLgMy\nn3vc6nDpI0fpDQN761zoVcvWfVpnOq9nPevhairWDiRFlEUAMJ0OAKCXLAKC0MM1N8VTj2Vy\n+9lsBU1doagahscyOchALU09X18doKicbpzUEl0mK0M5doSFXSkrk2OJ1/LF2Q21FUnUl/LF\nK9rjHEL7WS0Egjli+f2m1nvCwb/afxPRrhnDOC8SmyeWAYBGSMP47mRmZk1Vl1evh2CAjGHs\nxrHjbPyURGrf1c0HWK2KaX4hiiaGaVWB3p1Y9gpdy58HWtd1AvvFJ8yCr2HciVaEl9YPMOUC\nM28OkYpLJ56+w1q5xeQN465E+uV8UTBNGqGDbdZbQ4FtU3h0U+TZnR7Nz0viedH2QQxzS23V\nYJZdKSvTU5k/RzteayAV09w4tcNGEhhANjGzsYt4I2bni9d1JAmAsTZ+Rji4TFHuSKSfzOer\nadpBEktleRjLDGOZsTb+gNXNM9LZSjiQhyRPd9pfzhXcBHGRz+2jqHli+fqOFI3QJdUh2O7l\n3HYgDEJ/9bmv70i+Vii+VigCgJ0g7q8OVRzSiyRZxfgMt6P7lTjUxlfT9PxyGaDfgN523isK\nAPBQzTrxEwyAAD4oCudE2gcx9JxBDU9m88tlpZFhLvS6/+x1bTK5ticMZJlZ1VVXxOJHNLW6\nSLKMTdXEe1m4h2t2zTlkvwG9E/GTJF8UjYmm2aSok6IxDqFL/Z6r/L5hFnakhSub5glOe4uq\n/SjLq2U1YxguipgvSu8VSg9lsitkFSF4r7FuGMuuVdVpifS0RPpmkgKAmNbL2d8sQVSzTJui\n3hT0H++0v1ooBihqT46zkURKh5Jp2gjiqbrwaS1t/wj4PiwJbxdKQZp6OJO9xOexEcRRdhvY\nYWY6q+FNrA8QCHSAe5OZu5PpISxztdNuW/z9rGBtmeX+1rj7cz9+Ta9aro3YSz7699Dzh980\nyZXL1310e0ynm8hniVy26/9ULgskCca6DiRyOcvbr0pr1/x334N/VPV/ZXKnetzP7zaoVCx+\nKZa/K8ufCsI3ojS1Kri/1QIAdyTTKxRlZnXoj24nAJgYHs3kboonH0hnrgn4krp+TSw+gmOf\nq6+uJH+kdOOcSPv1scRJoWAju4sseBEEUYnk7p6cUPlwSaT927J0W3VootdjIdA8Qbw8GpsY\naV+w++BtSAyv7H+DqPEQRTWp2vS66oMc9n8m04vKEkOgAE2XdPPMrQlt6t54vKk1ih7SlV8x\nym4nETIwlhDCJMUW88zCb+fvNaaZ4WwEYbE7tTMn4s8+or6Zy8bazPrGrWo8RVF90fhKjgG1\nkZ5J0TDHr2lZIyvHuxx7WSwduv5yJndUU+vbAxv22+I5UqVndIzLiLDR6yzj+zK5AEV/PHRg\nRa5rlN12jNu174rV96ayQy3ct5JMUFR319q8shymKe+mFpG7Gt/VMw9kcg0s06Kohzlsjby1\nkbcO5/mRy1ZRCA23Wj4plir3WC1Nj7XbvitLXbfcffW1Kmp7JJN7JLNupStE06/vsdtgi0Uw\nDPQL45WxUwbi94QH09lb46kGhj7L7SoZ5kJJqpSkrRjQKmAAsKANJzkWAqm/rVCX3ieuaVaC\n6Fp+qdxwFddvh6aPd9jvrOqFJKjNc6LTfiBvfTGXX6modpLc32o50WHfVUvo9BvQOwsxRT2l\npc3EGACuDnj3tVoezeTuSWYwwDUBH4OQitDVAd8DqczsfPEyv3ey38sQyMD4kUzulniKJpBm\n4nqGtpPESAv3fH31YU2tj6cyAODrg6iysS7HC4n0N2XpLN3wkGRK1y9uizUrKgAQCA62WXOG\nCQB+ivyrz/N2oSSbuGAYcV0P0xQArFbUlG4M2ZSNOMZm+7gklAzzCDv/bF21481XlEjrv+oH\neUlytst37rkXjv3qC/qn7436Rm3YiJ6cAlJVy6vPdZnLRDZLZDMYAVA06J1Zd5IECHXFdZCx\ntsfrB990xB9yiIBYEgB+kqQfBHEQwMG89WDeep7HNXD56m/K5fEOGwZ4o1A82m77Y6fbjEBw\nsc/9brH0er54TcD3n5IomXhKVaBLSc1PkbeHAkevbX0nm/t7b+hz7wzQNG2xrCfrWwnsXlmW\nPi0K19bV3NBYV9l+gtNZ73TuvXDRq0L55vrabTgWQmiDqPHTg4H722LvSMrZ4dCR4RAAvJHK\nnL585Xmh4LbFl9u3fnEgpqhLxLKTIofzVn6zD6PD4XAAnO73vZRMndcaRRjOSEYPCzdcVz3Q\nhgjBMA7zuh0OBz7qWO2buZb2KDliZF83fsux2O2PxeKf5otxVR1qtZwXCnxaLK2Wldm7Dz2l\nc65yg6zs98NP18WT343acwt3+31JuGbR0i8LRcU0wyxzSTh0WXX4O7E82m67oiMpGuZIG39J\nOFTvYE7weZ9PpO4f1HjRqqZLO5L/HNjgp+mCblzf3LpALE9pqNvMFe/qGdEwVkjy/1VXPRjr\nyCCi8pOAqgFAXNfihulnmK792FhGK5e7/nQAzHY5vymWvsgXMrqxu9Vyit/roCgA4H85WEgU\nxS3sip2cNlV7syD8IEnvF4UGhnmuPrwbywIABriuI/lEJvcnt/NA3hqkqEohAgbBckW1IjSG\nt9oIolnVxtl4DBDVtISmD2aZ/njorcVPU2XTTOuGr5tgXKU+bqC3xQ821wyK/HsfZF7thPQb\n0DsLM9s7CobxdmPtaS1tK2R1csB3qI0/oyX6UDp7psu5SJJPcDoA4JV8cQTH/iPoq/yKROgS\nn2dKPI1MBICnJtL/DAcphCiEDrfxs9JZjiC2PHWmaGwYLa2aOGcaG2vlnuLzvZBIf1wSdlux\nxkESKsZvFkunOO2vF0okgGLiGamMmyL3460sQk6SLBoGdE6IV8jKxW0dDEJ/3JSC2LW14fFL\nV2AMBxp67o2XF5SEqWMOiWD0kFy6hLJ+Upb3O+JYqmkVteSnHhrQzDdzyY52I1xDxtoAAHMM\nkhWE4WfruUI3j51EUs9W1zfy1nt9ngVl+ZF0Nqnpxyxb+fnAhlqaAgA7SdAIlQwTAIqGUTTM\n3TZard6dY1/MyQAQ0zQAGMIwcU0nEFRUnypVIaJbrPC986MoSiWSe4NY/6+LAgDs3y0CHgBq\nAEI09V02n9n6KA6aph0OxwYpCpfYrf/h2HNWrJ4RiQ5hmCZVXVCWB7LMlS77ViUzMJ1m04pk\ncklZphAazrHu/yVrmtT1GzqSbxVKlXvIQRKTA74LPO7u/hgTw2pVfalQbDVxUZIJAs0tlQEA\nY8AALwVqXwrUkoZJglmnyud++FZ+9H5GXYOdJOV8Tt6yU+i7tJAKOkEsAnT+8tVtmlZFUwGK\nei0pPhtPWgnCShCT16x9JNI2weM8wWHnAc52OqanMssSicqoopoYEPxSaPKngnh2a7uNJCeG\nAnbDmCcI/2iOvBpP6hh/Wyy1UJSFQB/lcjPbYv+sDiJV1TE+kSZ/8LofT6ZeSqT8FJUxDAPj\nP7qd5/NcRyq9RlWtBFFH012XoKID3dUzQqV/VPVAq/XZePIsKzeQZQgMHIFUE74sFC/0uit3\njozxnGx+GMtscCMNBhjMr5sxGqUSuN0AUCgUNqMD3Uf57tuNuKZfG0v8u/Sz8GKLqh7e1HqN\n3/t3vxcBXO33PpnJ3ZFMr5HVjGEgQI9mco92+ukRgJMkEcAQjt1/VfPaztHveKf9tqC/dufL\n9N2BZA3ju7KU1I2BDLOPldsgqeBYu31mKnttLOGgyAVlqWAYA1kmpuo2gjiE36Kixf1sFf0G\n9M7CN8XSIJY5gLdOcDufyuZviifPdDkPsFo/F8pntLZpAOd5XADQompnuDb0o5AIVGxOcDtf\nzBW+L0tH2m2Kab6cLwLAbQ21vv/1ms8axh2J9DvFUk43nCR5rMP2j4CvQ9dvjicXlGUdYxdJ\nTvS4Lvd7uqo5HOJy0AiNsnD78taIqi6WlLWqOl+SAIAEmCOKgOHhmioOobRuONdlGeJD17Tw\nJNGuaiRCNTR9ZzI9weU4dH37/giX81SXY3aueFtZuW3oKABwm/pD0TXnLVl42TGn5wwTSNLw\nB4nChumAWwu9fIlR26CNGkO+PRsAIbkSpIi6hUEjYGhQ1S4PNIHx7B+/Yfb9P5qmrIh4JJ2d\n4PM8lkg9mM7eVRUAgJ8kWcW4ok1rIwiGQPGN4mdimuYmSQBwESQA7Le6OWcYAFBFU9cEfPtY\nLADg21mre/QilTPcYNEWA6gm7kW/k4skPx5Y/2A6+06h9E5RqGfoK/3e/+t2J285eV2/uqnl\niXiiIr3FEOgir+fqgPeX4ggVjE9uaVurqOd7XYfyvGCaz+byN3Yk87pxbecE+PuyfGUssaSz\nEhjRWRmkiqJPddofz+Ur2k8GQhTGbyVanR3t6NXntBF7gWGYrp1CZfyNQvHmeKrrPq+l6euC\nPgtBnNISFQ2TQ2gQyyyRlfMisd87bI/XhitrUFnD/FES7kqklysqAAxhmckB3/HrSzWbGCbH\nEjUM/fXokSGGyeVyhuG5P5WdmkgRCGpoesHgAQSC1Yp6QTT2f23xKpoewjIUQlOrAqe6HG8X\nhW9EsR7o3Vj2aAc/LZl5JJ1VMQYAH0X+I+g/y+3c+MrZCKKBoT8pCTOrQyc0Rw9rajnV6QjT\ntI7BBGwjiLM9TgBYrajXdyQTun53uM/XxHdyFIxPbomuVTUAONZh5wn0Wr4IAGGKmppID2XZ\nYxw2O0kgBN+K0qE2fm+OeyyTlTAAAAHAEUTZNPOGMYhhrmqP19DULSF/kKK+l6RnsoXvy9Ln\ngxo8/a5oAAB4OJ27O5kWOufAQzn2vnCwe9nOMVZuvMP+drGEAKpoigb0lSCZgA/hrf3u/L5g\n139P/yowMaQ0rWiYM1PZo+22lYrycDr3cHqdjdiiqlNCgUolWDtBZAwTABK6fncy819BzBhG\nxQi5Meg/iLfMSGUfzmQJQBRC1Qx9ZU04m/05qFcysWX9cKSErh/dFOnQtWPt9t1YZo2qvpYv\nvl8oiRg7SGKSx+mlqAWiNCOV+UIQ3xtQV/EV+Wj6VL/3pWT6B0l2UcQQhnGS3A+yDAASxghQ\nLUPFNeOwNS1L1hmmwCHkp8hK1ryfpAIU+XFJeD1fPMfjujcc7N6m8Vbr7FxxcqzVOWTo4Lmf\n7D94mPWY8YucDg2h+kIWwkEkCpjlkFBCxSJ2e7Bl6+fWGKNS0Rw0VBs0lPYHyXSq09Pc3aDD\nsL4nmDWNUFlQv/3yu30OuD+dAYBZ8SQCeC1fuNTrVjD+e3ucQ+gPTjsAkAgdxvNvF4W/ykqX\ngs/8svS5UK5Mgb6TZQDAgK8L+ghAbxeKl7XHB7I0geAY166vGru3hSMQvJYvdk8Z/EwQs4Yx\npledJSxCV/q9V/ZsSREDnLhk+ZeF4llu19F2XjPxG4XiA6lMh6bN6syPyRjGM9n8Ekm2EOQo\nC4sAVsrKwzVVp3bOeE9xOc5qbZuZyV7gdXsocoWs/KElagBGCAIUldT0dVo2GDp07RNRWDig\ntv31lxKYqFKkK4ftHR17ZN2Rx3Jvz6YX/4hJShu6ew97pue8ni9e1NYxhGOTunG4jQeMPxXE\nitgcAiAAIUAv1NXoGE9Nph5O517KF5crKonQG/nCjFS2jqYneZwEoI9KwqRI+2V+b9faGgAs\nU5Soqt1dUxXqVllttIUDgCBFRVTtorbYraHAYJa5LRQ4uSXaoqr3dlZuYhD6tCQslxUAWFCW\nnsvlAWCczXac0yaZ5iv54uXt8ZimXR3wwUZc7HVf05G8J5V5rLbq6Uz+5UJRMzEAhBmqQ9UP\nXt3CISRjzCB0U9A/vlfzs3+NvJwrrFZUK0Hsx1uerQt/UBReyxf3tnBLJMVLkU/m8sc4bA+m\nsiaGw238Kw01j2fyEsaP1YZv6EiUMT7Obh/GMatl9YV8oZqh366vrWVpADjV5RjvsJ/cHJ2V\nzt0Q3MRl2rXJG4adILrH8T+eyd8UTx7EWy/1e6ooaqEk351Mn9bS9vmg+gGdD4iJYaWiOEjS\nRxIRTacA9uUtVoQ+E8QvBHHsVuqg9/M/6TegdzxNinLh6rVLxTIA3JZIAQAg8JDEHhy3UlVT\nmg6AHsvk/uhy2klirI3/d7H0XlG4rD0umuYhvGUEyb1XKAHAfqvXPlkbfruxbpWi3pNIzyuX\nb6gKVw6xWlFvS6TmiWXBMGtpeqLHdZzT8VIut0rRVilKh65XqgxUZJ6+K0vjmyMWRHw1qHGd\n99oPT2fzk2OJZ3OF8z0uALi6qeWlZNpGEDI2k5qR1CQAOJS3nu/1XByNqRjHNf2WRLLrHAlA\nMuDViooApoT8F/o8CEA0zes7ks9m8wdaLad0c6uPEwteVX0zXPdCuGqEIsOiBVGn83LaSpvm\nafO/sKxdSaYSJs/bHv5n5ft64yBl3DGme2vStxECzoJKRSAI6fiTbU89vLkvYwwEUlirocpW\nw/hxxbJj3WGOIE51Oj4sCYJpFk1zzOpmwEAT8EBNVVcC3I1B3/jmyBFNrae7HINYZpmivpEv\nekjy6oBviay8nS/uzrHLZOX1fHG8wz7Obo1oWpOiTXA7h1l3/eW2EE2d7XY9m80bgCd6XA6C\n+FwQp6cyYZo6q/fmDz9K8rtFoVlR6hjmGIdt/23t2I8Lpf/mi3cNaDiP574Ty1PT6YWShBCa\nnS8OZNnLfZ6PSsLf2uMFw/BTpILxq/kCTxI2Ap3s/PnGRgATPa6PS+J3knSU3XZfKqObWAOM\nARKaDgAEAhMDiYBFxHJZ/WDZ0r/FolP32PuolUu/nvfRmiXzgWXJTAoAjPpG7NjBsywMcHsy\nPZRjH6gNH726OaXriyR5uIVbJismBjuJioYpYTwtmbom4Ls56H+vKPwrk1ujqPtbLQ+mc+Ns\n/DP11RX//U1B/1/aOmams6e7HF3VNNK6DgAbpJO2aBoAuEnyRIf98Wz+zUKpIkwEAENZpqLq\nk9T1E5ojMsb7WS1H2mxOEk3uSJIIFU39bLcTAZzncZ0dab8/nZ3ocYWYDYOsJnndSd2Ymcl+\n2FkM0kIQNwT9F3hdP0jypyWxTdMGMszvnfaG33B0gYnh6Xji/kjbEllBCMqmuaeFA4CxNquX\nJOO6rgFupJnlspLTjUq0xm2hAAD8KMl2kjjJac/o+nUdyYt87mEsMzmWAIB2VRu1em09Q18b\n8J3ichzMW4dz7H8FEX4zBnTZNGekMs/lCmndYBE6mLfeXhve1wEGxtOT6dFWy2sNNZWy9rtz\n7AiOPbopcnxzxE2Qg1nmKLvNBGhS1Duqgn/xulQTkwhIhATTHLZ8zZuFUr8B3ev0G9A7GBXj\nU9e0JnX9H/U1d0baBzB0h66LpllF0/tYLV+K5dNczhOctrNb2x/L5q70e68Jej8VxPOiMQah\nq/xeFeMns3kWoTqGWaUop7a0VXZrJYhbQ/4JXjcAfC1Kp7ZEKYR+77TziPhaLN+WSE1NpkwM\nVTQV1wwMeFIkhjCUsBmkqQN5K8agAq4snBkYP5srvFcUSEB3J1IYwz4u855o+2l+371+NwCs\nkNVVqjItkVmjquNs1jmDG25NpD4orHv3IEB7cIwOsKLTFf2RIF7k8wAATxD3hoOfCeLL+WJ3\nA9peLj+++NsJow85ZE3LPgfb1WljAAAgAElEQVQdYUkk5itQ5vh7V/w4OJeBTBIACNNUD/6d\n4XCRqQT9w3fWF54Qz7lgq0wKfcAgasVSItbOfD+/+3aMAOENvykf/Xvrkw8v5h17iMWLho+h\nDOOGqsB4h+32xro9f1pqQUTBMIay7PVBbx3DqCZmCAQAQzn204ENN8WTL+eLGsYsQic57TcG\n/VU0NTtfwABP11X/IEl3JzMzUhkAqKHpomHuwXFbcQP9mpkWCnAIPZnNv54vVrbsZ7X8szpk\n7wzEnyuUH0pnVyiqlUBjrJar/N4tD4jEADd0JP+VzWEMfor6d0l4KJ39o9tZSRL4pV9pGC+T\nlRZVq6XpPSxsV3jGPEEEgAvCwVdboxdFY26KPMXpkDB+PV+8M5FaKsmfCmI1Rb1SXz3aagGA\n94ul86MdeF0k88+Hq6hGlE0MAHOEcsV6DtKUgcHF0GvKEgAYGMrYJACWJFMA8IIv/Fio7oq1\nK/bJZwuq6qqqHZyM4Y3Mvj7ENJEoYN62QQGXNlWLqto/gr5KmvIiSf6rz3NryH94U+tiSR7E\nsD/KsolhRir7er400soVDTOqatU0fQhvnSeWrwv6urqXIdANQd/7xdJHJWEwu24mHKZpAFjV\nGd+y7psIAMBNklOqAme4nR8UhYimVVPUA+nMAbwVASwoS2e2thUM00qgZYrybVniCYJE6Gq/\nd1oyvaAs7Wu1kAhd7HV/UhK/EqWTN+pJBHBt0He62/GZUI6o6kCGOdJuq0Se7G3h9rbsao8n\nt/UDDkGSpyxd8VY6M5Rja2g6oasKhofSOZqiWYT+5Pc8lEgDwApVNbC57+rmvGE4KfJdsbzC\nMDQCEYAsHDeA5wGgHcO0to6PCiUA2MNqOcJh/6hQvLito8kwbq6u8jNMVFW7t5AkSYIgtqHN\nvUKv1yHujmSaJ65s+lEsj3Pax/DWuKrNzubHrmz6iGUdiMgYxlVet61zuXWZJE+ItJuAS7rp\nY+kPiuK/O+d7HwjCqX5vFbeuqaphVjNMh2FuVadV1GlIktz+XY0QYll2Y1WfPqXrym5wvpuX\nLeo3oHcw7xeFJkV5ftiQs4L+BtO8oj0umCaBUEXR+Wi77a5wwEYQQ1jm85J4pd87gGGerA2f\n0hKVMb4zmQaAvSycjnElUqISrOumiHurQid0FpW9KhZ3U+RY3vpRScjp6ySTTAznelx3VQWq\nlq6GrtQZgIJuvlUoAoCOsWCaJILTWqILynIDQ9tIVMb4+o5EIJ2lEHpocCMqFgFglJUbZeUA\nw6Xt8fmSdDBvnVVdVV9cBRgIhL4bMqCSYPdstnBlLI4A5grlP0faf5TklG4M5Vg3Sa5S1PtT\nmWZVa7Rafu/3Dbbbxydj83XhLn/1j/lC2mI9Nh2/smnpyGIeEADLgqIa/qBywKEAoAPow4Zb\nX3iS/XqufPTxW97z8kG/45ub+JeegvXTqtZZz12x0AiQUKKX/kQo8spw/VmjDm61WAFgcixx\nUzxVRVOKiR+vC13XkVyhKOdEYgDgJMmrA97zPW4CQQNDX+B1A4bliuIhySBFVeqlFUwTAEIU\ndbLTcbLTUalEo2M8dMWavPE/ZAczhvFTWS5hcxjL/qqL3zIEur0qcJHP831ZKprm7iwzymrp\nMjZvT6RnpDJektyPt4qm+Vqh+Ea++EJ99aFb5kd5Lpt/LJM71eWYWhXwkmTBMG5PpJ/K5gcy\n9GW/EM4xVyhf3ZFYo6yL26mlqWnh4NF2GwDI2EQACOCaWGJ3jn2zodZNkVFVez1f3MdqebdY\nAoC1mnZ8c3Qoy0wOeI9z2EdYst+X5cti8bPdrv06Pd9fiRIAVK5ayTQphDSMRdNUMS5KBocI\nuVPb0QRIMwxGqETTaZq9bfBwv6JErHyVLK1ta6HaWolsxvT0cqo7KhbIdBIQYQSCmLehUon9\n7yfUyuXI0IEk9YFDlN8daTrXabdLGAOAnSAaWMZJkgXTuNDjBoCSYQDAT7LSWacZErr+tVBW\nTTNAU18ObpiVzgLABnOhOoYGgJT+s6bbEJYZxjIPpbInhgWeJFcL5VqKnCtKAKBgEwMM59jh\nHAsAj2VyGoaDeatomhMjMQ0DgVDTsMEUQp8K4sRIO8ZwpN02LZn+SZIrMaN+mgaA4i9LyA1g\nmAGeX/HDtYUghP6nhaSamEDQfdo5O519K52ZXFt9Scg/vT3+YCxuo0hBN+7tSFS+UIm3FQ2D\nJ0gfTRdMo6Abd3UkAMBGkoJhLFC0laoOAOevjXTd80vL0tKy1MCxo238jHjq3KrQYkkeY+e7\nt5AgiC1pcx9B0zTZZ8HED7d3/CiWHx084M9Bf2XLjbJy8E/LLlm99oWhgwDAzrIcx2GA11KZ\nS5paSobhoWgT4+WyvAdvtRDou5IIAF+VyuNXrZ2/9/C30tnbo+1NsgIASUN/qySc4fdtoaBc\n5TR3iAENAAzD9IXg5maoTBg2vrU2n3Xdb0DvYH6SZQA4zuu+vy12XzxVMWRtBCoa+By3a3r1\nupA+H0XlOsd6C0EAwPRwcAjHcgjdHE99J0lTqgLv5EsCNm8O+SfHEpfH4gfw1moGXkqmVikq\nCfBqvogAAhSVNnQTAwJ4LpsvmAYGDAAMQirGf/G4PhbENg3rgAkEdpK4I5FeUJZvrwqc63Lt\nubppHM8fbrNeFUtUhsXuyeeVMN82VVuIpA9KAsaAEDTSdG2nJuU4uxU6c6Q+KImH2/iDSWKh\nJK9SVACYmkizCCm5wh2x+CSXc6bTNfibuTNPPM3yxb+R+HNyN3a4ULFgBENktBWVRWzlAcAI\nVhm1DWRL01b1PHa6yqecyT//RLdt3TIIu1UnJJMJMplY4g38dcieAUUGgEnRta81DCoZ5lpF\nPdHrejCdbdc0GqGZ1aEyxi/nCv/oSCZ048ag7+Z4alY666HIkRYupxsPpbMv5gpvNNbWUBQA\nLJHlMVYLAFTET/4riABQ98vORR3j6anMg6ms3Dm4HGHn7w6Haulf8YNcS1O1zg0DSReWpftT\nmeOd9pnVoUptwiZFPa217dL2+ILBAxgCSSZeqSgUQkNYZpMaDk9n8wNZ5sHqUCWO0EmSd4eD\nP8nK09lCdwNaNM1mVQvTVKuq/THS5iepu8PBYRy7VlHvT2XPjcReqa8ea+MHsywGeKQjnjeM\n+6pDFf2NSgmYKooEAITWpfn+pyRMjMQGMkyTqgLAy7niy7niwbz1gZqq78vSjFRmlJXbozMm\nnkGohqZaVd0EzBFkDU2sUX4erz/0V9UffkKaZgnAL/8wb4nddcPgPa9cuwIAQJKts58X/3wx\npnvHyEOyxM75hF7y47pkAILQdh9BrW1CiqQPG254fUQ2Sy1bbI00l886r2K419I0h9DXZekC\ngL3ttjn5wnEtkXG8tUXVCAADYx9JpQ39fI/r1ULRTpIZw7jY5bQRRBVNA8AaRe2e/1QZB8Lr\n38n311Sd2BwZvXBR93dpI8N8V5ZPao6e6XbyBPFRSXg1XxhjtRzvsL1RKCV1/Ugb/6komhgA\nwTgbf5Sdf6cgVPwCCGCZrMwTpTmCCACh7ajttXOCMc7n87/033eKpenJzCpFJRCM4Lhr/N7D\n7DwAvBJPWgniuUTqnmg7AAACodvMByFkVO4iBMc4+Nfyxf2slm/L0pku5/EO262J1CrT+MPS\nlWVsAkCAIiOaCQAkgAHAEgSJzYWCCADnrFiV0rTTbHz3FvI8TxBEqVTqm/74RXw+HwCUy2V5\n/SWRnrOwLM0Vpbiuf1YSa2nqZJbuOl8HwHle99SOhCiULAT6dzJ1AkOfG23/vCQCgJ8i07qG\nATwk+X5dtYlg9xVrDAwsgdbI8uAFP2R0YyjLHshbvhIlHtCfVjYtzOb/sWXxMA6Hg2EYVVW3\nf1d7vd5SqbQZ1Zq+gOM4m822ycehcuk3ya/4vbtrgAABwB+XrfxPNr+3hTvKYXsim5NNAABl\nnbUJCsYrFKXLiVWJS56Zzka0SnIL7MaxAxg6qmu7sew4G/94TdUxayMv5PJt6eyz6SwAGIAq\nemxjrFxaN3+SJRljwPBWft2zUUNTa1Xt8Wx+ktf1XLYAACaG78rS64XiAbxlosd1YzyV1Y2T\nnfYTnfYZ6Vy7qpWN9WZmlYqDs/PFuWJ5XToehrWq+mQm92evGwDCNE0h0DEAwP3h4OluJwDc\nGc9MV9IAcEvId4nPmyPIqYnUE4nU/gccdvYn71lfeAIwYJoGlkNCyaiuJdIpwBi7nJDoQPl8\nxYAGANNipbStlH7D2PLuG4AxJkhkVkb/yqC/6Wremq5/9dVHDXL5yt32jtqdR9ltA2n6fUGc\nky8VDCNAUyGKqgSinO12TorEZqWze7LsrHT2JKf9n51W4IKydFak/ZK2jpcbam5JpK7rSD5T\nF65EeUY07YaOpJ0kjrL/oof11njqkUzuKLvtHI/TThBfCOVZ6ezJzZH/Dmq07FpS9W8VSgRC\n91QFuyp7D2SZq/3eS9vjc8Xy12Xp4U5FBZ4grvB7LvZ5NjCFVinqaS7HBoVqD+GtM1IZwTRt\nBBHV9JviyX//rDFH0gAfDqirlCHY32oZ77AdvLrlzmRmrI3/g9s5pSM5PRoDgMp05VNBvDme\nqmboD0oiiZCJ8U0hP4vQTSH/iBVNTap6nN3+71KpUmFxnlges6rJwDCIZR6rWZeZwAASTTNI\nsc2qBgATgt6nOpLdW6sjIslww4Tii99/ZRDwvcMz95tPRheyq3j7ELEExQK1+Edt1L690N0Y\nW956lWyLaHvurQ8ZBiamly+hl/4EAOKZE83qdZrc5D77WZ57ovDlF+8eMq5V1app6liH/a1C\n8b5E+kCHY06+AICfyRUAwAQgEFRCk1UMtTS1VFarKeqvPjcAHGXnOYSujiUGsswaRWURGs6x\ny2WVIdCx6+fkNavq/7N33vFxFNcDfzPbrlf1aslyLxhsMGAMxPTeAoTQYjA99JZQQhIg+YUk\n4CTUUE0LkFBi4wDBYIKNwQ0XcJfVy0m63rbOzu+P1Z1P1bJcJJn7/qGPbm9v793slLdvXpF0\n6mBYHuOkrjkw9mtEovq9ed6nA6EVTUkAYBC6wu26Pz+HQWi7LAPAyXbbp/HE4ljcCOe9yetd\nGIm/HAoDwP/iyft87WnT+B3NPoTgEk+2+l0v/MrX/ow/VMnzcz1OjcInsfhF9U2/Lci7Ice9\nIp5I6noeRpe6XRro74SiXYKvU/MnAngvHJtqFk6yW30q+Uc48q9I1MMwmEKEdircRq3ZXJZZ\nWFH+k/rGekVtU8HG4DjR1yWl67zubrlZ0qxIJD+NJVpUrZxnz3M5B1fecqjYKEpvhSM7ZbVW\nUeoUlQIY5ZMYBP8IRy9JOTRSACNfUFQjl7tdfw+Ezq5tWC9KF7kd74SiLob1awQAgoS8Egrf\nmOPJYZlmVVMIBYCARgCgVlG2yfRYm/XNsuJrm1r/5g/+1O2s+AH77u9bsgr0EDPVJADAJ8Hw\n/eUlt9qtCKBWVv6XSALAJ9GEWkRlSu9paQtq5KJUNFJQ0xCCelU93W7XgX4UjW+V5EvrmwGA\nULo0lviR3ephmYWR+HeSlM/zbYoCQAWEFEoXR+NuhrFhLKYMBgiBm2GMJES5LPtyIAwAGJAO\n9IzaBkrBr5HxW6pjun6hy2G4hcywWZqC4Qfq6u9zdZZjjev6fH9QQOjLRHKux3VnnveUnfXN\nqkYBftHaXiXw0yzmnzW0aCmniM2y+nYo8q0kvxwMMQicDPNNUroJoE5RZtis/wuFf6kzF5x9\ngeW9twBj0Iie71ZPOFUdO4Hdutm86F9MSzMAQDr5BqWMr1l37dkqyNZW43AQAMBug0hk1xu7\ntOfMlHZQmYjFWM6qkvt3fP9CedWOsrLDrA6bSfhVYwsGaFe1W3I86Y9d43UtjsZeDocFhB4v\nKkhrgYdbzLfkeH7j6wgR/Y+F+be3tM3cXuNhuQjRRJ0igFvyPH3lbPJr5IVg+CyH7aWyYuPI\n0VbLFJMwt7HljVB4nndYJDXbV7SomofB3TIwGkmyH2nzfy9JZzjspzpsGqXvR2IPt/kbVO0v\n5SWZJwsYJXrsvsV1HQHwCPlU7dSd9WFCrvK6p5iEJlX9c3sAAdQoSrqOl4thznLaXwqGFJ16\nefadSeMu3LQNAM6va2QRCmmkhOfOdTie9AcMt/k3guGrvO51omRsFrUQFQG8P6p0STyxJJb4\nXpIu87j+UJDHpx51DrWY1iXFlUnRePlSV+3Z4Ja67QWSOCERIQhNjkUazNZbJ00vERN312wF\nAK62Zp8o0Gx9DdNYLx87R5l5jHFEq6yybd+MNM285CPi9pCKKnXSVJKT9/cZRz/o8EabfZ0f\nBGRnmEd87QLCANCsaACAAAkYOITiRAeAV0NhDhAA/LIgx3ABz2fZUx22DyKxzZLiYbCO6DpR\nAoCrPK7MvRSdwm99/rEmYe3hh1oZJhQKEUK+SiTPq22UKWwaV7VNlkWdTjDtqrhhwhgAfmS3\njgpwdzT72jXtVLvN2NaLER0B+igWd2IcpbqLYe7I9b4SCs9taJmWl5e/9414cLFZkp/1h85x\n2p8uLjR67K/13Evrmx9p6whqWoemAUCdJNdJcreYEQfGUV0v5bkmxbDv0I2ivFHsDIBRKW3X\ntPT5TgZLOpUp7dDIuXUNF7scC4IRASMBUJzopztsj3StnNesql5Nc3HcDU2t/wpHMQIXZoKE\n/M0f+nmOZ4C21SHn0Tb/X/0BBpAFowjRAeAws+mt8pJL6ps2ytJtza1VPD/RxD/REXwhEDIm\nsVub235dmOvXyHuRKAC8H44BQIOiXJfjftYfKuO5N8PRcx2OJoVYGfz7wrw7mttUSgFABeph\nmdfKigSM7s3z/ica+yyeMDIBZNl7sgr0EHOa3WZncJzoHpZtUlSKYKJZ+DyeBIAwISftrG9U\n1SjR53ndZ6a2uW9t8SGKdKCLo532YzuDY0S3MZgD/JOGpgWlxYpOaxWlgGN9qURsVQJ3Z07O\n7a2+tCuIMYvZMJ5sEhoUtUFRE7qOEOIAVKBAOzVJIxOtGeMfp9RlE0IMgvlNrcuD4QKWXS9J\nrYpGgLIIHWuzPFaUDwBzPe5H2jqMb/lxXTPNTA9H4Sl/AAAQAIvQyXZru0bqFPWc2sYViWT6\nrGd8rXcCqNNmcN+uUg87Qh07AQC0seMBYRSLUbPF8MVEmip8sQSHgtJJp+9RyzO1Ow1jM4pE\ndLcns4J3rzg11UzIy6Wj/l1QstyVE48m3osmjAbRAQSMFkZiYUJ+5nHls6yR6bldJUZtyMzr\nGF6b9bJysdspYHxjU4tPVc0YF3OMSGF+ezBO6JO9VYxbkxQ1Sn/q7jL3neG0u1uZlUnxIFOg\nPSwT0fWkrmcmbG5SVQD4XpJuz/Xcl3ITvMztvLmp9dVg+Kb83BkZGdKPtFg+iyd8qpZWiD+L\nJ94MRRwM/mVru09VA4Qsqig73NLp8fa3jiAG+JWvY8no8vRFbBjrFGRKbQCH2Wz/V1l+a3WN\nqsMRNvMcm+Vyt+tP7X4AoEDHCPz9vo6tspLWDtYlpSs9rplW80yr+bZcz6jNO1wY8xkbBdd7\n3ZcnkqU816h0rd2TwQ6LXUYIAE494vjv7a4QxwPA6+tWGO/iup2g67DnOa27gZsaAECdeljn\na0qFpf9FxhZqMs7Goty2zdz6NQtPOec2d4GJEA4hHqME0TWgnTWSELgxY8wtFKikgwQUAIz6\n1RMFYYMkmQD/orV9TVKM6nqdoowR+CKO3SDKsg65LCPq+qJo/DeFeabUpkGtojSr6sO5+Znl\nG2dZLRNNwrJE8v78nGmpeL7tsvJNIhkknZblf4ajb48q+XlT6wOt7Q+kHkummoRNkuJgmClm\nUx7DxKj+ejjiYphaRflTY/Mfc7NG6C58HItTgAfzc9M91oLxffm5p9fUz/d3mSoz53aMOsNp\n+unSNMMycZTF8nEsDgAsgjZV+1tHEABYioyKvAGNNKtaMceqlP49EPqLP2jE8LgYNky0a7yu\nX+TlOhjcqmr3+drndwTMCE0yC2MFYThbWBdHY/M7Amc6bLfnec+oaZxttZxos/2mvf0hX/sV\nHtetzT4OoacCwSZF3SBKh1vM60XJzjDtRPtpXdMTRQXvRaIzLeYqgf8gGiti2Utczmf9ISfD\nbJXk+3xtFOjVHvfJNpsObQDw7djK/yWStzf7VifF42zWQpYFAH+P0gRZBs3Br0D7VG2jJEmU\nThKE0cNvl4fHaIrZ9G1SunNnXfrgVLPJSCcXJuREm+0Kj3OWtTNX7tvh6DZJsTHoYpf7g0jU\n2KaJEZ0BJOn0GJuAZLirpc2wtFEAN8uGNA0ANknKVU0t3WybCBCP4Mt4EgDuz8+5McdTvnm7\nUduCR/Aju21JLE4A7sn1/jMcvb6pddWYilaNvB8MH2qzT7aY/9HRsUanAGDByM1wzaq6XpTq\nFNWInHspEGrRNOg6wwKAi2HCnQstaJQ2KVqrpsV1vQHUs1zOZfF4WCOQir6PjpvkrqsxLXqX\n2b5FLy5DkRBQHRBCYtL2zBPU5UKBAJIlbeLUXcv/wGAksatcPenydoLlrp1y+LsFpeZU4u3M\nM2SdrkqKq5Lis/7QX0sKA5oGALks3iIrhNJMRwKfRgDAzTIU4LF2v4th/jmq1HCKFXV6Z4vv\nhUDo/Ej0tLzcbtIoQAHgT+3+G5tbJV2fYBJu9nrOdNrNCMkHNt7iAHCy3fZKMPzH9sCvCnJ3\n7XJ0BHmMFJ1e6+2i7lyf43krHP0yFp+R0Wh35nrPqkucWtNwW65nnCD8od1vuCwXcOw7oYhE\nqZthppp3FZMfK/BNmrZBlIIa8aQs38sSyWKOszP49UDowZYtwc61h34eS7Sr6neS/Ek0DgBn\nO+x/LM7/la/jlWA4fSdOsFt/n7KfMQghANK1R53qsP2uMP/Xvl4Mz2k+yivkdaoh7BNMoZS7\nc47aac9DOmHra7WK0QNu197p1JVTzvfc9i382pWU5ZCmaoceIc+cxX+7Wl32+b2NLVQwaRgT\ngATREQIvZp0MJAG5WXZzUixi2SjV40R3scwMs3lFIpnUdQDYIEkAcENzKwU41GyiFCiFnYrC\nIWRMBRhwQqdxXXugtT2dy9mwvbl7BON7WKY9tYGm6PQBX/uroQhJDQETwo91+JtU9a683E2S\nuDAS3yBKR1jMDxfmnbyz/reFeetF6cVAyMMyEwUhoGk6hdfb2m902st3V3DqB4Vf0xBASVeX\n9EJuVxMZXhZM2t0ZAAD0gc1D6bM+ThUvNB47jeNq6iork+Kh23f+zO1q07T/RONHWc0neW2E\nYf+vxQcAuSxnQmhxNLZNVkwAGMHv2/3GB2dZLRc67cuT4kZRYhEq4biL3c5T7da+Cl4eSF4P\nRVwYR3X9hOp6AFiWSPo0bZbV8m4k9mhh3j/DluWJ5OJIDACMlDIAENQ0AMCA7vO1MYDGmYQ/\nF+XPtlpuaGr9SX1TKcdtEiWEYHE0jhC60uW6rqnVeALp0IiRuHOHrBxns26VFQAoGcZPFyOO\ng1mBlin9bWv7i8GwmhrhZzrtvy/IKxhmEVejTaZ1SWnRlAmr2/0+Tfs0Ft8odoYpdKikSuCP\nsnRqz4TS3/o6AOBmr/eOPO/qpEh0COsEjLWZwsexuKE3G2kHErrebRe7W8w5BRrQqPGRT2OJ\nf4ajafvZ30oKz3c6vk4kz61t+mN7cI7N8lk88dP65rVJUQdYE4utyYgtSOpUphoAxHX9hJ31\nk03CTKspqusWjJNU76anhnVSxQvVinyC3fplLLkhFZMxySQsCkcOs1rrQOIAxb05APDu+nU/\n+enPzMu/4DZ+C1s3dYrNcdrYiaDIOBYlo8doE6fuqQ7B1lYz27elZ/Ldmp8BQEbo1fVfJ4/g\nb3G7Tke9P4lhAC+Dr29ssWBcJfA/djruaGl7KRi5xutq07S/+YPL4+JORRYQ8mDmO1HaISuP\nFOalQ8rMGD1WlL8oEnvbH5zkcCzu8G+Pxko59kS7rYhjGxQFADZKUjnHywhXS+rcxpYLY45W\nVbvINeyeDPeSk+zW0x32J/3Bb5Li8TZLUqfvRaI+VTvWalmWSLq6GvUNe3+sa1c/zGJ6q6zk\nntY2I8UsAFgxeqK48DynXaZ03JbqECF/bA+kazT8zOO6s6UNABpU1cMyUaI/0taxNile5nb+\npK7ps3gih+N+VV56oVlYGos/1NbxnSTvkJXxJiEukTZNQxSeLC64Py9nQTD0544gi9Cfi/LT\nhXY/icYpwJQe8ezXeF1fJuIfRxMIkJPFYa2XpBAKRi+WjQYATKmg6wzQmSF/+l3+qy/2XoHW\nvbkAwDTUaRVVAMB+t45arKSwmN25nduwhvt6GSIqweyvt274+ZQZcxTxI5PNgnFS10NEc7J8\nq6zcWFj0YH29SGmc6DaMIxr5Ip4wY4QAzAgnqY4RqJRe6HI8XVJ4a7PPp6lehtksyT91Ox8u\nyHMweEkscUl906vB8DkO+2ybBQDKeI5FaE3KxcVA1On3kpyeEn/d1v5yMHyJy3FDrtfD4G8S\n4kO+9jaN/iMceSMUAQAGoble94P5OUZylY2i9GIgdJHL+VhRnhVjAJi5vbZeVW9pavn3qNK9\nbMaDiXyWpQA1ipqZ5+f98K45/5Opk9bEEnfV1JL98PDOIqQDpRRRSl8OhgHghhz3bwvyqmXl\n5UicALVh/If2jjfD4Tp5l6mbQeil0sJNovKEP/BVIpk2dG+W5P/G4qU8+0xJ0cyhTrG/TZYT\nlK5JSpe7Xa+Fwqc6bN+J8lcJUaf03paObxJJlJI7s13tDOYABQnhELwZCvMI/SLP+89RJQ+2\nthu1PIECi5AG9MjqWh3gtlzv0/7gA772O3K9AGBlGJ+qPehrt2BspBXKsk9ABzhXyD6HUhoI\nZGaDAI7jnE4nAFy8/vt3wpELXI6LnQ4Bo8/iyWcDwSqeXzK6nBvUkyjLsi6Xy+/37/7UPWGZ\nrJy/o3ZeYf51dusJO/Ckl8MAACAASURBVOt4hK7yuF8OhjBCk03CZ7HEDLNZwNCmkqSut2ga\nBjjJbptfXHDotpp0AqDBgQA8LBMiJNNyUMSxLaq2Y0KVgPAzgeCrwWizqiDo01yLAY6zWWKE\nrhHFPk7p7Yv7uFz6HS/D/GPFkqPC/m3TDp/YUIP9Hd3OIiVl4lkXUFuGtwOlbM0OprkJVEXP\nzdMmTKEcBwBWq9VsNhNCQqEQAOBoxPLCk0jXew0W7E2mXWGF9Wbbzw6Z+bXbC4AMUZ0Mo1Ha\n7UEFA3qypOBcp/3s2sY1SXGSSdgqK5mmGgzoXKftvUjsn6NKju+al+3oHbU6wg2ynH7wExC6\nKy/nKX8wrusapRggj2M7NGJckAP09diK8n7tCv3EEe9v4vG4EbcuCILdbgeAAY4gldKXguGn\n/MFWVWMQmmISHszP2S4rv2xtX1xZlpnA4d+R2LzGltcqyi4tK0nPBh9F4+9FovWqakN4i6QI\nGFaMqUg7hJxeU/+9JJsR3jqhypgLKMDRO2qrFQVRI1kNIZRW8nyNomAAjJCAcYKQE+3Wl8uK\nEcCsHbU2jL+oGvViIPTL1nYGAQLEIkQoVSjlEPp1Qe6PXQ4G4D+xxIOt7Q6MVoytNPWYeaZs\n25kgeozqmEJfg9lMyPUN1XfVbPYqSvc85QjFbroTzJY+PgqQMSUGg8FeszIhWbI+/yRwnHja\n2SQ33/rK3ynHMYkEKPKubI5AAUBimI0/+dmxwfj84sJv4sm3UsEDxtvpKGEekNJjhJsQUig9\nx+lo1dSVCZFBoFHIZ9njbNarPS6R6ufWNpoxnmOzvlLWGWd5VUPzR7HE02NHX12QHwmHOmTl\nzta2DyOx18uLT7HbokSfsK36ZJv15VRUAABsl5XZ1bWXupynOmwY0GSTYFhMkro+bku1k2FE\nqm8aX2XciBpFmbWj7hCbdW0svm5s5T43zjEM43a7ASAcDveTVWAIh6emab1m4aiWlWOq646z\nWl4sKzJCOIKEnFBd36SqDEIswCF263uTJpy0buMWSe5nddgbDB8/nQIBekOOp0Ml70Uimd0X\nAzxamPd4R9DFYIVCvaJMNpmsGKXjCvJZlkGoRVUBgEHAI7RqTOXgLGjGPUrPZoNm7JbqMCGf\nji6fZBImbd05WuAXlBZO216rZKwOxoKDAC53O18NRS7Ky/lfMNzWaYcGihCl1IrRXXm5MUKe\nD4Z0gGs97uWJxOqkdKTV8sfCvPEm4bVQ5O6WNgygAT3SbNkoSTKl84vyL3YPqFqCkYVDluUh\nycIRiUSGKgtHN30S+h2eB60CvT0pjl/17ZUe1x+LdsWHvBmK3Nrsyyyuu0fspQL9aSzxl47A\nZlkWEJphMf8iL8cwPQqCcFtL20utbXYGx3X9SItlrSgyAG+Xl65Jig+3ddCuCqdRrsyOcUyn\n3SYuBkAHoACZCWUBYIrF9F2yy7BHAA6GiRACAKc77EmdbJGUNk0zYXSkxfJFPPHvirKbm1ob\nVLWI41pU1Y5wjOoAcIrdFqH6ynhnqg1DmG6YMJL1Lh1LACQbPpEAGEGm0aLXydfN4AShDkV6\ncePKUzpa08cpyyBN3/UJzMjHn6hOOZSt2YF9LdyObciIC2QYIITa7eLp55GyUd0UaOHzT/i1\nK/u9V71TY7XNnXrkSpeX13WlD8dTBKjTZQXB30uKxgv8/a0dyxIJ410bxvGuGsw5TkdUJx2q\nFiF6UCdJfVfDCRgXsbhR1UiGE0wOy/o1jceIB2RcagzPrxhb0b/kI1GBThPUiIXBhsbToZHD\nt9eU8NzzJYVGTOGapHh1Y4sOsG7iuHyXMxAIqJRe29jyYTTuYpgqga9XlA6N5LLs6rEV1tRd\nWxAM39XSBgDrx48uZlkK8GYocmdL2wl26ziBr1XUco7TAZ7xB6/wuN4JRX7scb0wafzvGpp+\nW9d4S673wfycB1rb/x4IvV9R+kibf01S5DDCAEBBBYoBVQrcdmlXWpiJJuG5ksJ0RfdMKrfs\nKGK5bbLcfyMwVP/D1g031W9HtPuYkc48X50wuZ/P7laBBgCmqcH873+iZKLbcWq26HbHcsF0\n7oQZH67+YlbIH/TmFh0x5zCr6XtRVlKD31jyGQSEwql2+8cZi64DMzF914g3YySmPwVgRlgB\nSoB6GCam6zPMJp9KVqb6s18jF9c3bRSlXI7LZfBOWVGB3pLTWfF7VVI8o6bhGo/LyTIuhjnS\nYj7EbAKAY3fUOhlmUWVZt9/y27aOv3UEPSz+16iyfJZZmZQeam3r0MhjVRW37Kj5d0Xp0db+\nnkMGwchVoAFgfkfw0baOPJY9xmohQP8XT0Z0QimwCP25pPDOplZjFgr3nUv7AMAjrFD9HKd9\nYSRO+1DjM4fLaIFfVlFq3bgON9UjWdZzctVDZwwkAH0vFeg2TfsslqhX1GcDQZHS/1aWTxSE\n/2v3/80fzBwRHEZIBwKUAFTx/NdjK06paYhQulOUjHw+APBcSeEfOwLpdPVHWc3/V5g/0STo\nFM6srV8rSpe4nCfZrSqF5wOhVUnRjrGXZQ41m+7I9fY6BfVKVoFO80NUoF/xtc/duuOjyrIZ\nGZYqRaejtuy4zO18rGgwUdcDV6DbVO1bUWpR1VKeO8JidjHMb3wdT/qDxRw3y2qRqb40nkjo\n9HqvW6U0ROkUpyOX4+6prk3otIhjZ9ks9+Z6mzXtrJoGF4PDRMcIRnFciOghQlgASFl60hiJ\nnLsc6sMs0PMwBtB7ZG8zykZc6XE5GWZ+R2CKSfjOqNUCAGkdcWBgBA6MOYQ7egwJpqsyDQA8\nIKM8G04ljb6/etODO75fn5N/SCKCRAmMYoGQIW6mFo+QesgM6fgT2aYG06eLQZISV99oycvP\nVKBtz/8V9Z36tC9Wuzz3jj90pctLBrx9gRGiGQPMjDGh9Gce12Fm0/OB0NqUo04Jx7Wqas9V\nCCFwYubxovw3w9ElsTgATDDxX4yueCkYesofMiLqDOZ5XA9lRF/1ZEQr0N34TzR2Y5NPorSC\n5zRK6xXVzTILyopnOx0OhyMQCDzjD/3K135TjseodUcordpSHdf167zudFA/ofSYHXXViuJm\n8DhBaNa0RkWdYhL+Nao07QB9ws76pK4vr6oo37z9Yq97weQJAPCjNes3itLWCVX3t7Y/Hwhl\nCuZhmT8XFZRy3Hl1DUld1yk4GWacIFztdZ3tsDF93J0Td9b7NdKs9hl0xen0D9vWz6uv5qku\nYUwRMndTWRCSjz5WOepY6OMrdm+BFkXhqy+4jWuB6IAQIJSuLkRcnnfOu2RBNPFFUrQSrUxM\nbrU5ug1+BFBqEhokGaWycfU6Oxgj+hS7tUFVt0pKz3OsGFUJgkzpsqpRuy7OMO9LyqehcFMy\nOYbnL3U707UAnw+G7mvZ5UGOAC5wOR4vKjhlZ52DYT7soUBrlB6+vTZz4JRy7F9Ki5oY9pYd\nNV9UjZo0YPVigIxoBRoAlieST3QEN4oSAzDdYr7E5Zjb2AIAZzjtt5aXLWhrX+gPxMhe7YIO\ngl4Wu745zW77VpI6VE1P+W3f11zzq42rqdlCTWYcCVGE5DmnqNNm9H+dvVGgXwiGH/F17Nql\nRMBQgB5rX09G8VxSp2FCCFCWIhlRoGB01N+1dTzREXx3VElmYakwIQ+3+V8PhY310IzRrbne\nW3I8g9hyzyrQaX6IeaBlXQcAa9eMYBxGLOpMK7E/oADvhCIPt/nbMu49h1Auy7aoai7LHGk1\njzXxhQx7hsN5a1PzU/4gC8jG4n8GwzxCFEAH2qSqKxLJLyzmlQmRRyhMdADQKRiZ5hiENEpx\nDzW454TSl5KbPsgipFEKsGvjOPOihnH75WAYAVgx/k6Sjdx2tMs1Uh9E/T2JMYDDRGd6fgq6\nBKB0/pDUaTrApHh4k81lbFj/ePIR3335H3Pqp3XZWc6wgVOG4davpjwvH3eCeNYFltdf5L5f\nD3NO2fWliTjKTFo3YA6PBD9dubTGbL126sxtNluQ27XWYui++W60pE4pAmRncIwQw/Zsx7hF\nVSt57oYcz7zGFuPkNk0jAA7MRPUuipGAsB3he1rblo4edej2uEZhFM+rQF8Mhv2adlee93CL\n+Sd1TQDwQjAco/TJ4oJB/K6hZW1SXByLrxclFtAMi/kil2MUzwHAOlFamRSjhIw3CafYbULG\nAnC6w768yvRMILhNVhmAC12OazxuN8tUS/KGZHtzJPpCIDRB4B9KRR8yCJ1kt/47EvtHOHpP\nXs5WWQ4TwiLcrhE3y5SynJ+Q8QJ/k9d9pceVWW6tRlbOdNoZBJPNps+jMUnXtydFC8ZBQlYk\nkm+HIwAwQRC2K8p3YyurFfXe1rZrGlrsDE7ouk7hOKt1gySuTCZXJ5NPm8035rjPddq7rWMy\npYUct0Hsc0lmKfWq0h0TDt1sdTy6fYOzVz2bUuGr/zGBgHjW+YO4BSgWs77xEoqlBgWl6UdT\nkWE3ALZ89MGRDs+68qoIy2+x9bJ3RwEaZRlSYcF9fZExRpbEkgToBEHYkmF0t2Ec12mC0o2i\ndFnXPDMMQvMK8+cV5htp7NLHmxT1YZ8fARxhNb9WWhzW9ecDwecDYUnXtyvq1Z5ekqmzCF3r\ndf/K136p2zmK58cI3Al2mwbol7UNhRw7QdjH2vNBwDFWyzFdrfLHBy1fJJKLI7HFGzcJGMkD\nDBvcpwxce8YIvVBa+EIw/JCvAwBUAi5NW5BTeM85FxppnXA0YvrwPdNnH+vFpSR3vyQz/CAc\n+2VLmwkhK8YlHBfTSauqdQbR94BBmGRsHddlJDMxwpxMgIwcI8dYLU90BLvtZ7oY5s9F+ffl\n53wvSmaMJwhCtxxQWfYtB60CPclqAYAv44nM/Oqrk6Ko0wn7rTTlfa3tLwRC0FUTVSk1fLA6\nNPJuONrtIwRRI3LImBQwgnlu94pk8o5mH4uMAigAALNtlgKGbSfk62SSUND7nUGMb+cQpI08\nboYNk2426+5LXV+XpKlw+O7BgF0+2588KtWhRwoC6JGdoxsYKKsDAnpJSz0AHBX2m3XS48Eh\nbXg20iMhI58Av/orbfxEUlgMZgvuyLBRiaL1tRd2/VSGBdBhYBaUepNtiTd3p83B60Tu6r/R\n8/MZzyHUqGzcmYxW1xdHEx9G4wh2qVLGxlym9jzObKqVZEnXR1mEZXFxeSLpZtgOTVsZF18N\nRqpl5dmSwrOd9tua2yiACeOLXY5Xg+E7c73DOX9TN3QK9/naXwqEaOqeLo0n/tTuv8TtjOr6\nh5FdZg8LxipQTacUAQvIyeAo0VVKvSxzntM+1+2yIHxva/uCYDj9PObA+NukOD21+3Rnrndx\nNB4lZOK2HXLm3dLBSIzl18hpDnuC0PkB/6fReKtG8lhGpbBFlpfGk4UsszYpepevTKaWq3Nr\nGwEAA2yRZQTwm3b/A3k5/ygvPnRbTVTXHy8quK3Z97+U344OsEmSrm1s+SzuNB5ywoQ84w99\nEY+vl5T+x7KGkE8wHx4OTI5HfLyZ1am1j0rv7NbvmaNnE2/35C27xbT8cxSLGDtQymFH8N+u\nInn5THsbAJiJdkgstIQvWOHOYXXK60TBvaeqGGg0QWoe2KLs0p7HCfz5Lsez/lCIEApwnH1A\nfhQvhyKSrp/rtL8fiT3a7r/B674nL2erpHwYiwuA+srq+DOP6x/hyJuhyDlOuw2jv3QEXg9F\n2jXt5bKSg6sS0f7ijfKSE2vqt0gyAMg67aPq1HBBp7Rsc3V66ZFBnx4Lr3DnbCuvrDSMKaGA\nNmYC09LEL/tcOu1cat5nIYaKTqsVZass39jUCgASpUDpbj21SLegph77xRijDo2U89hIROPs\nrWiAl2GOs/VZjSvLPuSgdeHQKUxbtbZGVh4ryjvf6WAR+iqRvKXJF9bJyjGVOYPKWNS/C8cm\nSf5RdZ2bYYKETDebinluUSSW9jMeOPskIMOOcWy/GdoPGIKuU6DbvvhPgSxus9nHx6MaQmw/\nJi67A8eiRhNSl0s88Qzz+2/R3Hw441zz2PGEkOQH/+RXf70XUz4KsPxjoyc8WTF24I4c/ZDe\ni0QIEIBOoTMrMILxZsvWZNI44bZcz5P+kE5BR5QHIBRd7nV9GUvUKAqP0Gyr5c68nNNr6p8q\nKbjI1XuAyDB04XgpELq3td3GYELhjlzPTKvlWX/oP6nU5jfmeK7yuBZF47/1tfe8WwgAAdK7\nPj6ZMJ5XkH8yz59X10AAAGg5z/0yP7eIZb+XpOcC4Xpll1MyRkinlAV0rNWyUZL8hECGQ1Ev\nbk69+fojABaBCoApOBjmzfLi02saOIQ4hJIZo8+4rLFN8ROX8zKP84r65hDZs+wFJp1c21B9\nR822ArnPUF1SVJK89Kqex/t34bDN/wNSZRBMIHcawilGKPVrKaAkiz/KLXmjqGxJToG61zmn\nMylhuWaSjpXtbPY7cr2/zKiIYcy6ANDNAn1RfVOdrCwfU3FXs++tcJdKePfn5d6W16dXa0gj\n/9cReD0UNhy4J5tNfxlbNY2SvrzD94aR7sLRKxTgzUjs6UCoTpRtDFCKIjoZCkv0HsNRep6v\n8V+FpQyFDcs+rkx0tWeZLeLxJ2mTD+n1s/24cDC+Fm7TRhQMUJudVIxWx018Oxz9bZu/XdNY\nSs/3NR4eDmoItticW+yOcjF5aDg4IR5hAC3Jyf9PTmGrxZzE/Zky03E1CIBBcKTF8mZ5yVm1\nDXWKumn8aGH/5ObLunCk+SH6QAPA2lbf5fVNWyQ5HXGVyzLPlBQO+uGsfwX6iY7g79o6OIQo\nwIZxlTO218yxWZcmkumS1wwgAjSdBdkgHVWWw7JBoo2IaejAYCPaSR2t7xeUvvjdN5c21Ru2\nDjTY5ws8fhI6/2Ll+SexLKFo932AAfKNO+f1oop3C0oiHK/v61nLzeKQppfzXJOqEWroMJ2/\nNJdlOjQyy2r+JikBUEKBQ5DLsqKuJyhdNKqMw2hOdd384oJL+4iwHoYK9LE7aoOEtGnkpbLi\nsxw2AKAAP6qu2yTJALBybAWlcNSOuvQ2xSiebVFJevd2P5m+uuW1zYTDSN3D8ZkO6s0EIeAB\ny3uYP+ewcOj+nd8fH2yzakTDiO1DEspx1GoHoIAxdbq0iipl2gzOZOqpQCNN475exm/4Fond\nAwcz0TD2Cab1Ds+LJZU7bbbtll5K/OwRmQNYQMiMkQnjgKarVHcyOEL0OTbr26N2FZXsU4Gu\na6xV1NVjKwFgkySvSIgBTROp/rQ/1DOzTU9USusUNYdhvDzn8Xj6Ca/cGw5KBRq6PpKdUl0n\n6nS7JPXpxT9smBoLNZhsAiVtvOmctua3v12e+a7u9uJwULzgEiOZYzf6UqCFL/7Lr1kJCFGW\nRZoGup4wWz92uiWrfQKDpuzYyg1gpIc5/vzps1e4d9MNHAwGQFFCilmuWVP7mfD3nqwCneaH\n6AMNABUC//no8nfD0TWiJOv6ZLPpJy6nY7+5BBnZzgnQXIaN67qo0zECvzgah9SaYcYorlOZ\n0swlRE+96+/aXfZTYqARRJxh3y8ovapxJ0vgF+OnPVD9vU3TBtMqPE+nTtfXrUKvPs8EAqAP\nPmb8yJD/yJD/b5tWaxiJmBEZVkFYxlhmmBXu3D9XjK+zdF+2B6LnGQ9RCUIBoF5Rz3TYP4zG\nMnf2OzTiZPDLpcXrJOn6xtYQISqFFlUbK/AvFeUfZjH9pSMAACPIiZMCVCvqKJ6LEP10e2ej\nIYAKgTMU6DVJ8fN4Mq09Oxicx3J1ijZO4LfJCmT4DHAIVAoA4MzY7TEeVgchWF/aM2TUd9iD\nq/V2kFKQ+0xY1yffutwXTJ/NUDo6GVu+YolD711dQaramYgGAMIhpnYnt2GtctnV4MxYaDWN\n37Re+OwTGMDmGKvrJWKyWBJPb2tSGMZwKVmUVywxeHo0WJFIqBhVWx3LXbmf5hbssNo1hLyK\ncmywrVRM1lpt//PkRdlOt6J0usD05KZQeovXszgW96naeEHACCJE/laUdAq7dag4xGxaGk9+\nL8mTTcIkk2DE/93Q1MogNMW8eyc9DqExw6+u1kikSuA/CEefKyu+qqF5qGXpDwT0O7ub1/Xf\nbt54+6TD/pNbqAPCmWUUQwEAMH/wju5wUZNJ93rJuMlq2Sjo5iZBKVu9jandydbX4lgUDJcq\nSlFqg8sqJi7o8VAaRTiGsIcSc28zjEtVPv/ms58cdswH+cWZxw3bcz7PRzTtKo/rGX8wZT8A\nI5Pj3jVJlr1lmCrQhJAFCxYsXbpUluWJEydef/31BQWDCZBiEbrY7Rxg4sO9pIjjAIBHOEQI\nBgQA4q5tUICUF6xK9XTIHQNIo5RJBfNlsr+1Zw6QOuxV9BIpeV/1phJJPNnfGuR42+AeSRUF\nrfkaAGhT4z6RCgFwOuV0zZEhz6RY5KrGnQ+MO+SJinGZJ/elj2VqeKMFboMop22rn8cT3Z6f\n5titfyoqcLPMHJv1i6pRR+2osWB8b17OT10OQOjVYPhP7YHpFvOhlv3l3N+NvR+eKOW+wiKU\nmZ5CSvk1aBQ2S7v8Ba0YG+1TzHHbUvmbEMAJduv3kuxTNQCIpR6NHAx+s7zkzJqGvfiJwwiO\n6ggAUchTpFtqt/28fgcaoO1d1wEAB/ymv/zBaMpB+0UiShGAiRAAqNJit9duzXx3Yix6tq8J\ntsJ2q/3TnILLmuudWuc9audNd0089J3CMsjIX0lTmyoU4I/tASMewITQekmyMDhMSI2iVO1O\nu73K434xGL6kvunX+bmzrJYwIX8PhP4Vjl7pcXl7cwz9QbGvFtCBcLnb+XYo8lIgVMLxTarC\n9PHcOORQQABwaXP9tY3V06PBF0pHywzuntAGADQNB/0AwLQ0cd9tSE+pxgjiAAYeZaICdGC2\nnmFXsxYGaBQQAFTq6klK0kO7fK/xVLlg/QrnKRd2PU4BwK+qZztsV7idzwVCU03COlF6s7x4\n4r7OGJNlEAzTCM0XX3zx66+/fvTRR1955ZW8vLwHH3xQ3p33/ZBzhtPGYyQgUCj9eXNrMcd+\nHI1nTuRG+TSNgp6q7UyAGqkwGNgvbkz9MPy1ZwBoMlkmHn/mLZOm/zen0M8Jw1NiHRAF+Dwn\nn6H091vXn5qRtbobmfeYRbsObhC79O2kvsu5d4rJtG7c6LfLS0pTyf+LOPb1shIWobtb2iq3\nVJdv3nFnS9s4k/BiaeEB60P7ZHgeaTG3qSSu66tSVQ+CGlmX2h6daBK4jN/TqmpTTAIAtGc8\ntFCACo4Pap3u6GkDcYzon8VEgAM+qPYPKsJ2VbuzZsvWLz68uW77QLXnoaBcTN5Uv6PZZD7z\n8OPGH3fmj6cf0y6YXln/zXGBdgyQzqVVzLEfVOzKMWdoCetlyYzR9R43AAykNH0hx75VXmJB\n+Pqm1inbds6urnsjHLnM7Xw0lanwh8yBXECPsJgfKcxbJYrNqgLDVXvGqS2fj3Lyfj55RkUy\n8cz3q3vRnvcpHECOTo5SpevEUImmAICb6o2Ye1VwRFEX1cswmAi6PiqZ6KmTOVnmGKvlorom\njkKIkEKOHT9yNhsPboajAh2NRj/66KPLLrusrKzMYrHMnTvX7/evWrVqqOXaDWUc9+v8vJiu\nI4CVCbFZ1eozkvsigDDRUarF067nRrBRr9vNe7/88wixI1yLGJVMjEvEZoU7psQHk3vuACAy\nGAFQChvtbh2hG+u3930uMlQIlKEizEiZjW/J9RRn5NBgEdxZXLhkdHlJj7pZs22Wr8dU/KEw\n72K3c57H9UJp0X8ry4u5A5R/Y18Nz7vyvAR0DOjS+uYn/cFXg+GTa+pDpNO3/M1wNNMjRUDo\nnryccp7LzH2GEfo4Flco7WaMMSH8UjAIAGiEd34AsGsqpjTA85/n5IfZ4ZhihWY0Mk8JQSjB\nsktyCuos1g/zik+a+aMgz99bs1kH0Cg9zGICAL9GHm3zAwCLwIQQICjk2Llu1/qxo2sVhUdo\n1MCSyRxhMS+rGvVqWfH9+bl/Ksr/3+hRTxQX7KeYqhHEgV9Ar/W6l1WNuiXXe6TF0k82+iGE\npjQdn9nyQunoijln/3J878GC+xYeaBKwAPQcNTFbTYYQPlIVFYS+4szdlnwdYwAolJO0x6wV\nVLU7W9rCOrEyuF5RHy3Mz2aMGSYMRxeOTZs2EUIOOaSzf5vN5oqKirVr186ePXtoBdst13hd\nMyymB33taxJSN52Ypv4a/2S6QKaKeHWPXtp7Q5OHZTu0EWFr7pNas/X9gtJpkWCxKA7PScNC\nCACMTcbeLyidEg9NifWp6NN04r6UhwYDsF1WjQN/7eh0XTVhdEmO96HKUUUMjvSRstqG8VV9\nJOra3+yr4TnDYn6rvOSWZl+zqv3Gt6tO+3SzuYRnXwmEMrutTOmRO2o1vcvGp05po6rOsllq\nZSUzJa1IdbPxoLpnBX+GI7GU0vyNK+fqqUe+t3YZHmY/CQElCDFGMhkKW+yOGZGgSScSZgAg\nxPFf5had2NYEAIUc970oA4CDwUa6Fc0oa1eYd4XHJVH6t47gB5HYZW6ndcC5PniMTnPYTttf\nP25EMiQLaCXPP5DKnbIgEPlVW7uo6wUs26aRfvKfHjAy8ooiAGCoflfNlgPz1ZbUaj9Lk75l\nTa2YKSVqHeYQdAl1wroOADsttvScxSN0jce1VlZWxZM60CjRx5uEZ0sLdxsgm+WAMRwV6NbW\nVp7njchrA7fbbdSQM3jiiScWLVpk/M9x3Mcff9zrdYzw532O1+vt590TAU4sKVYp/ToS2yaK\neRznZNlmWWlTlKXh6NexaJQQQikGhGmnH4WhNhNKLZhJ7kWIW098fZc3GylBiirGy905940/\n9PnvvhkbP9DhwAPBcF/TELJrKgAoAzDApB+UigThcIftlqJCJ8v8NxRuVdRxZtO5Od6ClANo\n/51tgPQMK94bdjs8a2trr7766vTL22677ayzzsq8QvpHnef1nllWujIae62tI0JImSDMctjP\nzvEggI3xxIpoF6NL/QAAHoRJREFUbIsovuZrNxKlJ/pIkvBVPIl6bKUdbncsiUT6iQgcQTBA\nT2lvvblu2zEh/3DTng1wRjtLDIMotRBNSmWMTiAwcoY0KioAYIQ6NFJlNt1eUrQjKT3T6ruz\npe0P/mBQ1TRKT/O4n5o41tabE3Nml9vn7KfFIo3T2WccTiLRXxaUQbDbEXr77bdv2LDB+L+y\nsvL5558f9Hf12m53eL0/qyh7rKn5q0jMJCuNkkyA5nGcBhDUNAbgaIftm0hCRd1zoB+YValM\nTK5Y8V9vRlLLAwMCcFM9hhgvJW2GmTn1ayUGm4iuIew3mU0ITbZaL8r13l5SZLh6qhS2JZN5\nHJd3ANP8G7ulgiDw/IGOtUUI9TNe9vdXd1tzSb9+PsNRgRZFsds9M5vN7e27ymFIkhRNZSLj\neR71obL0dXwvGchleYSOczuP6xq8eGdZcbfTEoQwCNWIUruqTrBY3Cx7e3Xtsy2+/frInlFQ\ncATAUJgWCV7YWj8mHh9qWXpHZBmrRtY53ef6GnWKvuktFRGPsEq7JHEoFYQlh0wam1Fnflpv\nIdX7qQ/vDbsdnrquRzMSBSqK0u1XZL7kEZrtcs7ukb76ELvtELsNAP5aVfleR/BFX9uaaFSh\ntMRkuqmg4Mf5OU82tywKhL5PJIxKJASAAWRmcJwQAPhkzzNzDV8ohFl+s81VLEmVyTi7h/nv\nDgAUGcVBgQJMiEU7eFOI7ewhZkLm+Ns2OlwAwCE01W493GY/2mm7JC/XKPp4U0nha23t25Ji\nAc+f5Had0fe+yn4dC/t7oPVz/X3+1bsdoclkMj1CE4nE3gjQ12e9PPeHylHG/z5Febyx5dt4\nAgBm2G23lxTl89yGeOLW6tr/hSOp6wClkMtzP8nLnWgxN8mKi2FWxOL/7ggMLp1OTxhKK8X4\n/E3fnuD37ZMLDoIIYnJ0rRWz7i57achEdACQzr2IHHl0z0/xCKYMndV5SNagIVz4+lmtejIc\nFWir1dot4kFVVSODrMHxxx9fVFRk/I8Q6vYEzzCMyWQCgGQyuW+zXGOMzWbzvjUYEIDRLDvR\nagGARCLxWHH+Y8X5PlVdHIpWyxKlkNT1Do00K4qfaKJGw0TVaKfVEwFCiOpdt6l75k1DCPJZ\nNqwRqbNw90hRngEAOJ1MjUfObG8ZakH6xKoRHdDxgXa3qioI/7FyAgI42+W6Jt8bJfqL7f4m\nVaWUTjabZ9iscULMDD7ebjvUagGq99WXBEFgWZYQ0jNp/5Cz2+Hp9Xpvvvnm9Mtx48YZP5Nl\nWUEQYM9NbqdYhFMqy7ocUuS7c71353oBQKO0UVZZBGVms9kkvNvUel1dQ1gnCJCbYThAbZo6\n7FTOPYEgpGBkIZrI4DDH5SjDLpwap2aUZpOlREo2m81jk7GdFvukWOQPW9YXS8knp838cuLY\nqRZzulK6nEwaP6MQ4J7cXSafnn3DmHUBQBTF/ZGqGSFksVj2+WJhMBDh1b73CQfHbkfo+eef\nf/TRnYqa0+kcxIq2R4usHeChglyAVI1MVUmoShWCxWMqQhqpl+UKk2DHTEwn3erqXe91wagS\nAKCK0vr5Jx1btz1cNbneYjHpBFPIVURMmVmhtotb6x2ausNqr0rEjfQvQU6w6NoGuxsBnRCP\nmHQ9zrBu9UCbnA3iCNuoDgDfMUIMIReCEMJHapnlkChgTM+7yDTpkJ73gmEYQRCSyeQBFBkA\nwGQyMQyjadqBz99gsVgkSdofg70fOI7jeZ5S2q2pKaU2W5/pAoejAu31elVVjcVi6THv9/vH\njduVHeyoo4466qijjP97LaRijO19fg9YljWbzaLYZyWwwSEIgqFYpK/sBPip3QJ9lLQllPo0\nLZdheYwAoF3T1olSjOgTTMIkk6BSulaUqmXFjvGJblcHwz7f0FgtK/lW5ni71cMwT3cEa1TV\nxTAn2W3nOGyPdQRWxJMSpRpQSkFLTYcsIC1DFcdgPItRHiFNp1pqtw0BmBlMdJD2g2GM1/Vp\nsfCERIQlOhrGej8G6lGUFpPl7sOOmlpWtrgw32I4cXJwUllRrx/pvxexLMuyrK7r+7yz7T27\nHZ4ul+vKK69Mv4zH48av6NnP9xUFAEBBVWSzSTjezG+b0EsdBINlieT6pBTW9TpF4QA1KlqL\nqopUTxCqgE4PlF8TAkoBDXDDGgFssTvfLBplJWSUlBy27lcUoRIpqbo8Y6LhDV9+ZByUGWbN\nUcf+8pjZCEAdVK0NY9YFAEmS+t9OHRwY4/23YDMMYwgvy/IBKwyx2xF6yimnpP8fdCGVfbLI\nmgDGYQSKIgPwAP3MC+7jTvQcftRbdTuF9d+i5s4MlZTngTEhSQSg0yPB9MkeVQaAmeFdJc/c\n+tBozxRBAiEbhVrMfshbMUAj5qZo8iGaDCyrjh5PiotJ5Vjd8ITpbWLkOE4QhAO/EHAcxzAM\nIeTAf7XFYjmQ48WAUmrs2/T8vSNMgZ42bRrLst99953xlByPx2tray+55JKhlmu4wCCUmXIh\nj2UzE6pzCB1pMR9pMQMAzzKlNmu3vE7dQhBeKu1dwwMAUafbZJlDqJznbBlhPWaz2Wq1dnt0\naVJUP9FiRKcAY0xCjOhFLGtl8LqkJOp6Bc/ncwyDENPUwO7cgUOBBMfV2V0+s6XdYp9us1ao\nkrxuzbZorEiMsxp86/I0WK1JBo+JxaZFQ4Xq8DLEUoaRrHa1tNyem4spyIqilY2yF5c++wNI\nQDuih+dsq2W2tffn0p4ECRE1GiAqg/EaUflKljRCvwyFRKpzOnhkOYeIDkXzqMrEWETErMag\naZFQkmVUxIxNRA+NhDSMlnrzOnjTzLD/0EioVTBzVLcSzaTrnK4DwHaL46P8okazWQY8Rkx4\nFXFcPMZQGmc4F1GeKh/TwQuzgn4TIRyFSjGhUxhe2jMyKiuacV6e7PZoVeO0yjE4GGBrdqBo\nRHe5tapx4xxD4874g2VEj9B+oBarOnEqf/hRKB5L1teCxUa8Od2rnAAAIbi9zbzkP9g39PuW\niEIOJV+z5tW8yckwxQI/sTC/3GKRPF4yZhwVDlDm/iz7ieGoQNvt9jlz5rz22mujRo0SBOHp\np58uKys77LDDhlquHxxmjKYNoKaXQQnPlWTkmC9M9azDulb3ICVlpKQMADBAJUBl6rgGwFSN\nO8xkMplM4XD42K4XN/ZUECFM0M+tWoHbWrAkUsYEsohUCfZhAXQEFLO6N1eZeRSYrZRhSXEJ\n9OVkD6BbLJhl5cHWBh+J/HCGp4dhgIFiYAHgUIf9TocDAAKBQO971pSieAwsFsrsmlQ5gNNT\n/4sA7miE2uyAsRr00x3bkM9XYbdeZ7ZAcRkOdJh8PiUvhyCEVU0382xH21OtdTihUruJCmbs\nb0ayvjd1NPcERBmEGI643GCz6rwZGIZUjdUKS3AsggMdOODX8/K1sRMoy0GqYHU01TK6x6t4\n9kHwa5bBcfCPUIeTjBrd57sMoxcWJS6f19f7ejDw70Uf+qKhiUQ7U92XrhGU4QBRhLCel6dO\nmUYcLmBYPSdvPMtOZndNC8POByvLYBmOCjQAXHvttS+//PLdd9+tadq0adMeeughPODERlkO\nVijDaLn52hnn7ekHrVar2WwmhGSGomcZNNnh2QsIUbuj/1NoyhZLPDlkZpdgU7ayinO5Iv5d\nm877cMuZ4zgjqj0YDO6lowKx20lRyT6SK8v+IjtC+wF7vOelfMwGntcpJycHAOLx+CDiUoap\nmpVlrxmmd5bn+euuu+66664bakGyZMnSnezwzJJlOJMdoVmyHACyT6VZsmTJkiVLlixZsuwJ\n9KBj9erV06dPnz59us/nG2pZBsTHH39sCKyq6lDLMiDeeOON6dOnz5kzZ6gFGSh//etfp0+f\nfuGFFw61IAPloYcemj59+g033DDUguxLPvzwQ6OfD7Ugg+Hzzz83hE8kEkMtyx7zzTffGMJ3\ndHQMtSx7zIYNGwzh6+vrh1qWPaa6utoQfsuWLUMty75k1apVxu9qa2sbalkOEDNnzpw+ffoH\nH3ww1IIcIG6//fbp06ffe++9Qy3IAeLtt9+ePn367Nmz9+hTWQt0lixZsmTJkiVLlix7QFaB\nzpIlS5YsWbJkyZJlD8gq0FmyZMmSJUuWLFmy7AHDNAvH3lBQUGAUQrNah6x8/B5RUVFhCDxS\nMg1NnDjxyiuvNCpRjQimT58OAF7viMlNO2vWLK/XW1paOtSC7EtGjx6dWaFwZFFeXm4Iz7Ij\nb84sLCw0hLdYBlpEZviQl5dnCO9w7CZL4DDE7XYbwns8nqGWZV8yonvU4LjiiisIIWPGjBlq\nQQ4Qc+bMqaioqKrqs6rrQcb48eOvvPJKoxjhwEF0d4Xss2TJkiVLlixZsmTJkmZkmDyzZMmS\nJUuWLFmyZBkmZBXoLFmyZMmSJUuWLFn2gJHnz9eNhQsXvvDCC90O2my2N998M/PIkiVL/vrX\nv2YemT9/fmVl5X6XrzcGIgwhZMGCBUuXLpVleeLEiddff31BQcGBFXMXkiQtWLDgq6++EkWx\nuLj4ggsumD17drdzhkkLD6Tdsm07hHz++ef/+te/fD5fTk7ORRdddOKJJw61RAMlHA4/88wz\n69evZ1l2zJgxV155ZUVFxVALtXuGVW/fU0Zom6cZub19txxMk1L/jOgRNAh+OHfW4Nprr734\n4otPOOEE4+We3e79k5R6yEgkEldfffULL7zQ7fhrr702f/78IRGpJwMR5rnnnps3b159fX0i\nkXjqqafmzZsnSdKBEa8njz/++A033FBfX59MJt99992zzjpr5cqV3c4ZJi08kHbLtu1QsXz5\n8gsvvHD16tWiKC5cuPDss8/euXPnUAs1UO65557777+/o6MjEok89thjl19+eTweH2qhds+w\n6u17yghtc4MR3dt3y0EzKe2WET2CBsEP5M5qmtbQ0PDss8+eddZZS5YsSR/fo9t9sLlwPPfc\nc5TSSy+9tNvx1tbW/Pz8IRGpJ7sVJhqNfvTRR5dddllZWZnFYpk7d67f71+1atUBkzCTeDz+\n5ZdfXnrppWVlZWaz+fzzz6+oqPjkk0+6nTYcWngg7ZZt2yHk9ddfP+ecc2bMmGEymc4666zS\n0tLly5cPtVADoqGhYcuWLddcc01OTo7D4Zg3b144HN66detQy7UbhlVv31NGaJunGbm9fSAc\nNJNS/4zoETQ4fiB3dsGCBTfddNPixYszD+7p7T6oFOjNmzcvXbr0qquu6plhzefz5eXlDYlU\nPdmtMJs2bSKEHHLIIcZLs9lcUVGxdu3aAyJdd1paWggho0ePTh9xuVyqqnY7bTi08EDaLdu2\nQ4XP52tubj7mmGPSR5588skrrrhiCEUaOI2NjRjjsrIy46VxjwghQyrU7hlWvX1PGaFtbjCi\ne/tAODgmpd0yokfQ4PiB3Nmrrrpq4cKF77zzTubBPb3dI94HOpOXXnqpqqrq6KOP7vmWz+db\nunTpG2+8EYvFKioqLr/88smTJx94CQcoTGtrK8/zLpcrfcTtdodCoQMuKQDA2LFjFy5cmH4Z\nCAS2bNkyb968bqcNhxYeSLtl23aoqK2tRQht2bLl8ccfN4wcF1544bHHHjvUcg2IWbNmzZo1\ny/g/EoksWLAgNzd36tSpQyvVbhlWvX1PGaFtbjCie/tAODgmpd0yokfQ4PiB3Nle2dPbffBY\noDds2LB9+/Yrr7wSIdTtrWQyGYvFCgoKHn/88eeff76qquqBBx747rvvhkTOgQgjimK3hN5m\ns1kUxQMraS/U1dU98MADJ5xwwsknn5x5fJi08EDaLdu2Q4Xhvbpw4cKbb775lVdeOeOMM/78\n5z+vXLlyqOXaMx588MHLL7982bJlJ510kiAIQy3Obhi2vX2PGFltbnBw9Pa+OGgmpd1ycIyg\ngfPDubO9sqe3e+RZoD/77LO//OUvxv933313OmXBokWLKisr07b3TCwWS6adb968eevXr1+0\naNGUKVOGRODdCmO1WmVZzryIqqp2u/0ASNurwIYAb7311qJFi+bOnXvaaad1+8jQtnCagbTb\n0LZtr4yIth0E3TqSrusAMHfuXKO61amnnrps2bJPP/105syZQyllH/Q1zzz88MOxWGz58uXP\nPvusyWQ699xzh07G3TMMe/sgGFltbjCyevtuGcQqdnBwcIyggTNyl5t9wp7e7pGnQJ9wwgnp\nhCNpIpHI2rVre+599wpCqKSkJB6P7wfpeqFXgfsXxuv1qqoai8XSd87v948bN27/Cpqip8Ch\nUOiRRx6JRCK/+93vBlLb8wC3cJqBtNvQtm1PRkrbDoJuHckIxchMCVRUVLRz584hkGwAdBP+\nueee27Jly/z58wHAbrefdtppy5cvX7t27TBX5oZbb98jRmibG7jdbhg5vX23DGIVOzgY0SNo\n7zmI72yv7OntPkhcONasWfP/7d19TFPXGwfwU4TRIlhALS9TqGM6UBc6U7DNyGyYmwFnFhAk\nOiFGlsUsC3OCDP3DEU0YjjBYlDiH4JA5CjWLAt0i27IpL9nEbS6TNdampSjVyWupLdhC+/vj\n5ndzg7z0KhSK389f7Tn39jw897Z5OL33dGxsTCKRTNjb1NSUnJxssViop3a7XafTCYVC18XH\nMhiRSOTp6Ul/b/Lw4UOdTrdhwwYXh0orKiqyWq3FxcWTVXjzJMPO5A25nStr1qzx8PDQ6/V0\nS1dXF32L2DwnFArv3r07MjJCt9hstsDAwDkMyRnz7WxnxU1zTnHrs31aC+ZDaVpu/Q56As/O\nkZ0Q28O9QArov//+Ozg4eOnSpRP2xsbGLl68uKysjFpPtLy8fHBwMCkpycVBOh+Mn59ffHx8\ndXW1wWDo6+srKSkJCwubqzetWq2+efNmdnY2n8+fbJt5kmFn8obczhV/f/8tW7ZUVVWp1WqL\nxaJUKtVq9fbt2+c6Lqds2rSJx+N99dVXJpPJZDIpFIrbt28nJibOdVzTmFdnO1tumnOKW5/t\n01owH0rTcut30BN4do7shNgebo7D4XBlfLPk/ffff+GFF3JycpiNR48evXfv3qlTpwghnZ2d\nVVVVKpXKbrevXr06IyNjDr+FmSwYZsBWq/Xs2bNXr14dHR0ViUT79u2jvhN0vYsXL1ZWVo5r\nXL9+fUFBwTzM8GR5Q27ng7GxMblc3tTUZDKZhEJhRkaGSCSa66CcpdVqz5w5o1arvb29hULh\nzp073eLm9Plztj8BN805xa3P9mktmA+labn1O+gJPDtHlhAyMjKyY8eODz/8kL5CidXhXiAF\nNAAAAACAayyQSzgAAAAAAFwDBTQAAAAAAAsooAEAAAAAWEABDQAAAADAAgpoAAAAAAAWUEAD\nAAAAALCAAhoAAAAAgAUU0AAATtm8efOyZctme5QzZ85wJuHp6fn0ccrlcg6H09LSQreYzeaC\nggKxWMzn86mfLMnIyLhx4wZzL4lE8uz8oi8AwLRQQAMAuNrt27fT0tKCgoK8vb1XrVp14MAB\nk8nE3KCkpMTxmNHR0RmPRKPRrF+/vry8PCcnR6fT9fb21tTU/PfffzExMV9//fWMDwcAsDA4\nNZ8BAAAzRafTxcbGikSiK1eurFix4ocffnj33Xfb29t//fXXRYsWuTISs9mckJAwNjZ27dq1\n4OBgqlEqlSqVyvj4+Pfee08sFrvRr2cDALgMZqABAFzq2LFjFotFLpdHRkb6+vqmpqYeOXKk\npaWltrbWxZF88cUXGo2msLCQrp4pnp6eeXl5NputoqLCxSEBALgFFNAAAE/i+vXr27ZtCwgI\n4HK5IpHo9OnTDoeD7v3xxx83btzI5XKXL1+elpZWXFzM4XCoC4sbGhokEklQUBC9sUwmo3aZ\nqdGZLl68KBaLeTxeQEDAtm3b/v33X7rr3LlzXC43OTn58b0SExMdDkdJSQmzsbq6esOGDT4+\nPnw+Pykp6c6dO3TXhQsXZDJZYGAgj8cLDw9PT0/XaDRUl0QikUgkcrlcIpH4+Pj4+flt3bpV\np9M5kytCiFarTU9PFwgEPB4vOjq6tLTUZrM5nygAgNmAAhoAgLWffvopLi5u5cqVKpWqr68v\nNzc3Ozt7z549VO+lS5cSEhJkMll3d/eff/7p4+OTk5NDdVkslt7e3vDwcOarmc1mQsijR49m\nZHQmhUKRnJwcGxvb2dnZ0dERFhZ27NgxqstoNN66dSsqKorL5TozaFdX15EjRwoKCh48eFBf\nX3/16tXU1FSqq66uLjU1VSqVqlSqBw8eFBUVXbhwYdeuXfS+169f//jjjwsLC3t6ehobG1tb\nW1NSUqbNFSFEpVLFxsYODAw0Nzf39/fn5+fn5+dPWPEDALjU4/epAADA415//fWlS5c6HA6b\nzRYeHr5u3Tq73U73Hj9+nBBy+fJlq9UaGhr62muv0V12u10sFhNC/vrrrwlfee/evYSQ0tJS\nh8NRXl4+2cf1wMDAtKMz43z06FFwcHB0dDRzrE2bNhFCmpub1Wo1IWTLli3O/O0bN24khLS1\ntdEtH3zwASHkzp07DocjJSUlJCSEGc9bb73l4+Mz2b779+8nhOj1+mlzFRcXJxQKh4eH6Q1O\nnjxJCGlsbHQmbACAWYIZaAAAdlpbW/V6/e7duzkcDt2YlJRECLl06VJbW5vBYKCeUjgcDj3h\nOo7dbj969GhlZeXq1aszMzPp9glX4fD39592dOaL//LLL/fv38/IyGA20tPG1KJ4Ti6NRwjx\n9fWVSCT005CQEEKIwWAghCgUCoPBQMfT3d2t0WjGxsbojfl8vlQqpZ+uXLmSEHL//v2pc6XV\naltaWrZu3cqcI09MTCSE/Pzzz06GDQAwG7AKBwAAOyqVihDy0ksvMRtDQ0MJIXfv3qVmdset\nmkyVjOP8/vvvWVlZ165dk0qldXV1vr6+Tz86s5G63HmySJYvX04I6evrc2ZQQkhgYCCzZPfw\n8CCEWK1WQojD4aitra2vr+/o6Ojq6uJwOGazmbkxn89nvhS979S5ouIvKysrKysbF0xPT4+T\nYQMAzAbMQAMAsEPdxObt7c1spK5j9vb2pnq9vLyYvVShSRsaGsrMzJRKpVqt9tSpUy0tLStW\nrJiR0ZmN1BwwVa3SLBYL9cDX13ft2rU3b96c8J48vV7P4XCo6V4KsyAeJz09/Z133nn55Zdr\na2t7enr6+/sTEhKYG0y279S5onrz8/Mfn4yvrq6eLBgAABdAAQ0AwE5YWBghhLmOBCHk1q1b\nhJB169ZRy2vcu3eP2UtNtVL6+/tfffXVs2fPZmVlaTSaffv2jatxn2Z0ZuOqVasIIVqtltnY\n2dlJP05JSXn48GFDQ8Pjo3z33Xfk/9dLTE2v158/f37Xrl2HDh2KjIykrgkZ9w/DZKbOFTUz\nTa/mAQAwf6CABgBgJz4+fsmSJTU1NcxGhULh4eGRlpYWFxfn6elZX19Pd9lstrq6OvrpRx99\n1NHRcf78+dLS0nHXNjz96MzGzZs3+/n5ffvtt8zGb775hn68f//+kJCQvLw8o9HI3Kanp6eo\nqCgiIoJ5WfZkBgcHCSHMlaRNJlN7e7szf8vUuYqOjn7xxRcbGhroWXNCSEVFBYfDcf2a2QAA\nTCigAQDY8fPz+/zzz1tbW/Py8np7ey0WS1VV1enTp3NzcyMjI4OCgg4cONDY2PjZZ58NDAx0\ndnbu3r2bnvft6+uTy+VpaWk7d+6cjdGZW/L5/JKSkj/++OPgwYO9vb2Dg4NZWVl6vZ7eICAg\nQKlUGo3GuLg4pVI5NDRksViamppkMtlzzz3X0NDA4/GmjWft2rVr1qyprq5ub28fHh6+cuXK\nm2++aTKZRkdHBwYGpt536lx5eHiUl5ePjIzs2bOnu7vbaDTW1NQcPHjw7bffpm+FBACYEyig\nAQBYy8zMrK+vb25uDg8PX7Zs2YkTJ8rKyj799FOq9/jx4ydPnqysrBQIBGKx2MvL65NPPiGE\nLF68uLm52Wq1yuVyzmMmXMj5CUYft6VCobh8+XJoaGhkZKTZbK6srGRu8Morr/zzzz+JiYnZ\n2dkCgUAgEOTm5u7YsePGjRtRUVHOBOPl5fX999/HxMS88cYbAoHg8OHDe/fuVSqV/v7+zz//\n/NDQ0NS7T5ErQohMJmtra7NYLFFRUaGhoQUFBXl5edR0u5O5AgCYDRzHJD9eBQAAM6WwsPDQ\noUNGo3HJkiVzHct8h1wBwPyHf+IBAGbS8PAwj8fbvn07s/G3336LiYlBRTgOcgUAbmpRfn7+\nXMcAALBweHl5GQyGmpqasLCwiIgIk8l04sSJL7/8sqKiIiIiYq6jm1+QKwBwU7iEAwBgho2O\njhYXF587d06n03G53JiYmMOHD1O/oQ3jIFcA4I5QQAMAAAAAsIBroAEAAAAAWEABDQAAAADA\nAgpoAAAAAAAWUEADAAAAALCAAhoAAAAAgAUU0AAAAAAALKCABgAAAABgAQU0AAAAAAAL/wPL\nFeD56m0XywAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 6, repr.plot.width = 8)\n",
    "res_mat %>% \n",
    "    ggplot(aes(log2FoldChange, -log10(pvalue), color = padj < .01 & abs(log2FoldChange) > 1)) + \n",
    "        geom_point(shape = 21) + \n",
    "        facet_wrap(~group, scales = 'free') + \n",
    "        guides(color = FALSE) + \n",
    "        NULL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison to Wilcoxon\n",
    "\n",
    "In this artificial example, donor and batch are fictitious, so DESeq2's GLM $\\beta$ estimates should not be that different from the Wilcoxon estimates. Here, we'll compare $\\beta$s to auROC, which is essentially equivalent to the Wilxocon statistic. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Removing NA values from labels\n"
     ]
    }
   ],
   "source": [
    "## Wilcoxon on CP10K normalized counts \n",
    "exprs_norm <- singlecellmethods::normalizeData(pbmc3k@assays$RNA@counts, scaling_factor = 1e4, method = 'log')\n",
    "dge_wilxocon <- wilcoxauc(exprs_norm, factor(pbmc3k@meta.data$seurat_annotations))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 10</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>feature</th><th scope=col>group</th><th scope=col>avgExpr</th><th scope=col>logFC</th><th scope=col>statistic</th><th scope=col>auc</th><th scope=col>pval</th><th scope=col>padj</th><th scope=col>pct_in</th><th scope=col>pct_out</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>AL627309.1   </td><td>Naive CD4 T</td><td>0.002385006</td><td>-0.0041459259</td><td>674621.0</td><td>0.4986566</td><td>0.2969381</td><td>0.5033193</td><td>0.1434720</td><td>0.4121587</td></tr>\n",
       "\t<tr><td>AP006222.2   </td><td>Naive CD4 T</td><td>0.000000000</td><td>-0.0025103485</td><td>675393.0</td><td>0.4992272</td><td>0.2993548</td><td>0.5033193</td><td>0.0000000</td><td>0.1545595</td></tr>\n",
       "\t<tr><td>RP11-206L10.2</td><td>Naive CD4 T</td><td>0.002616515</td><td> 0.0001829296</td><td>676017.0</td><td>0.4996884</td><td>0.7459480</td><td>0.8712226</td><td>0.1434720</td><td>0.2060793</td></tr>\n",
       "\t<tr><td>RP11-206L10.9</td><td>Naive CD4 T</td><td>0.000000000</td><td>-0.0018526156</td><td>675393.0</td><td>0.4992272</td><td>0.2993548</td><td>0.5033193</td><td>0.0000000</td><td>0.1545595</td></tr>\n",
       "\t<tr><td>LINC00115    </td><td>Naive CD4 T</td><td>0.007142957</td><td>-0.0051776178</td><td>674127.5</td><td>0.4982918</td><td>0.3475021</td><td>0.5567626</td><td>0.4304161</td><td>0.7727975</td></tr>\n",
       "\t<tr><td>NOC2L        </td><td>Naive CD4 T</td><td>0.155593344</td><td>-0.0060562808</td><td>668592.0</td><td>0.4942001</td><td>0.3741228</td><td>0.5813188</td><td>8.6083214</td><td>9.9948480</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 10\n",
       "\\begin{tabular}{r|llllllllll}\n",
       " feature & group & avgExpr & logFC & statistic & auc & pval & padj & pct\\_in & pct\\_out\\\\\n",
       " <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t AL627309.1    & Naive CD4 T & 0.002385006 & -0.0041459259 & 674621.0 & 0.4986566 & 0.2969381 & 0.5033193 & 0.1434720 & 0.4121587\\\\\n",
       "\t AP006222.2    & Naive CD4 T & 0.000000000 & -0.0025103485 & 675393.0 & 0.4992272 & 0.2993548 & 0.5033193 & 0.0000000 & 0.1545595\\\\\n",
       "\t RP11-206L10.2 & Naive CD4 T & 0.002616515 &  0.0001829296 & 676017.0 & 0.4996884 & 0.7459480 & 0.8712226 & 0.1434720 & 0.2060793\\\\\n",
       "\t RP11-206L10.9 & Naive CD4 T & 0.000000000 & -0.0018526156 & 675393.0 & 0.4992272 & 0.2993548 & 0.5033193 & 0.0000000 & 0.1545595\\\\\n",
       "\t LINC00115     & Naive CD4 T & 0.007142957 & -0.0051776178 & 674127.5 & 0.4982918 & 0.3475021 & 0.5567626 & 0.4304161 & 0.7727975\\\\\n",
       "\t NOC2L         & Naive CD4 T & 0.155593344 & -0.0060562808 & 668592.0 & 0.4942001 & 0.3741228 & 0.5813188 & 8.6083214 & 9.9948480\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 10\n",
       "\n",
       "| feature &lt;chr&gt; | group &lt;chr&gt; | avgExpr &lt;dbl&gt; | logFC &lt;dbl&gt; | statistic &lt;dbl&gt; | auc &lt;dbl&gt; | pval &lt;dbl&gt; | padj &lt;dbl&gt; | pct_in &lt;dbl&gt; | pct_out &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|\n",
       "| AL627309.1    | Naive CD4 T | 0.002385006 | -0.0041459259 | 674621.0 | 0.4986566 | 0.2969381 | 0.5033193 | 0.1434720 | 0.4121587 |\n",
       "| AP006222.2    | Naive CD4 T | 0.000000000 | -0.0025103485 | 675393.0 | 0.4992272 | 0.2993548 | 0.5033193 | 0.0000000 | 0.1545595 |\n",
       "| RP11-206L10.2 | Naive CD4 T | 0.002616515 |  0.0001829296 | 676017.0 | 0.4996884 | 0.7459480 | 0.8712226 | 0.1434720 | 0.2060793 |\n",
       "| RP11-206L10.9 | Naive CD4 T | 0.000000000 | -0.0018526156 | 675393.0 | 0.4992272 | 0.2993548 | 0.5033193 | 0.0000000 | 0.1545595 |\n",
       "| LINC00115     | Naive CD4 T | 0.007142957 | -0.0051776178 | 674127.5 | 0.4982918 | 0.3475021 | 0.5567626 | 0.4304161 | 0.7727975 |\n",
       "| NOC2L         | Naive CD4 T | 0.155593344 | -0.0060562808 | 668592.0 | 0.4942001 | 0.3741228 | 0.5813188 | 8.6083214 | 9.9948480 |\n",
       "\n"
      ],
      "text/plain": [
       "  feature       group       avgExpr     logFC         statistic auc      \n",
       "1 AL627309.1    Naive CD4 T 0.002385006 -0.0041459259 674621.0  0.4986566\n",
       "2 AP006222.2    Naive CD4 T 0.000000000 -0.0025103485 675393.0  0.4992272\n",
       "3 RP11-206L10.2 Naive CD4 T 0.002616515  0.0001829296 676017.0  0.4996884\n",
       "4 RP11-206L10.9 Naive CD4 T 0.000000000 -0.0018526156 675393.0  0.4992272\n",
       "5 LINC00115     Naive CD4 T 0.007142957 -0.0051776178 674127.5  0.4982918\n",
       "6 NOC2L         Naive CD4 T 0.155593344 -0.0060562808 668592.0  0.4942001\n",
       "  pval      padj      pct_in    pct_out  \n",
       "1 0.2969381 0.5033193 0.1434720 0.4121587\n",
       "2 0.2993548 0.5033193 0.0000000 0.1545595\n",
       "3 0.7459480 0.8712226 0.1434720 0.2060793\n",
       "4 0.2993548 0.5033193 0.0000000 0.1545595\n",
       "5 0.3475021 0.5567626 0.4304161 0.7727975\n",
       "6 0.3741228 0.5813188 8.6083214 9.9948480"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(dge_wilxocon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LvjaCb5o3AAQAZjF2DRgUfSPYDW6/Xy8C+JpQygGY1sw3GcBgF0cneB1+tty8bp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PIcRisZw7d+7xxx+XthQAaNbatWt/+OGH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\nBgAAAABIw/8DEUMFUzPlthoAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 6, repr.plot.width = 8)\n",
    "dplyr::inner_join(dge_wilxocon, res_mat, by = c('feature', 'group')) %>% \n",
    "    ggplot(aes(auc, stat)) + \n",
    "        geom_point(shape = '.') + \n",
    "        facet_wrap(~group, scales = 'free') + \n",
    "        geom_vline(xintercept = .5) + \n",
    "        geom_hline(yintercept = 0) + \n",
    "        labs(x = 'AUC', y = 'GLM beta') + \n",
    "        NULL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the results agree, more or less. Interestingly, the Wilcoxon labels almost all genes as upregulated in DCs and CD16+ Monocytes and downregulated in Platelets. What's going on here? It turns out that DCs and CD16+ Monos are mRNA rich cells while platelets are mRNA poor cells overall. DESeq2 is able to account for this effect better than CP10K normalization. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YkTJ3DqyBMnTgwfPpzzdsM5Dlq1aqX0HvHqoMViQQitX78+Ojqa4yCjlNzc3D17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\n",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.height = 3, repr.plot.width = 5)\n",
    "pbmc3k@meta.data %>% \n",
    "    subset(!is.na(seurat_annotations)) %>% \n",
    "    ggplot(aes(reorder(seurat_annotations, nCount_RNA), nCount_RNA)) + \n",
    "        geom_boxplot(outlier.shape = NA) + \n",
    "        geom_jitter(shape = '.', height = 0) + \n",
    "        coord_flip() + \n",
    "        labs(x = '') + \n",
    "        NULL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pairwise tests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Instead of 1-vs-all, let's do pairwise test and then summarize statistics conservatively. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>seurat_annotations</th><th scope=col>donor</th><th scope=col>batch</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>sample_37</th><td>Memory CD4 T</td><td>B</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_48</th><td>B           </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_10</th><td>Memory CD4 T</td><td>B</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>sample_2</th><td>CD14+ Mono  </td><td>A</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>sample_51</th><td>NK          </td><td>C</td><td>B</td></tr>\n",
       "\t<tr><th scope=row>sample_1</th><td>Memory CD4 T</td><td>A</td><td>A</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 3\n",
       "\\begin{tabular}{r|lll}\n",
       "  & seurat\\_annotations & donor & batch\\\\\n",
       "  & <fct> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\tsample\\_37 & Memory CD4 T & B & B\\\\\n",
       "\tsample\\_48 & B            & C & B\\\\\n",
       "\tsample\\_10 & Memory CD4 T & B & A\\\\\n",
       "\tsample\\_2 & CD14+ Mono   & A & A\\\\\n",
       "\tsample\\_51 & NK           & C & B\\\\\n",
       "\tsample\\_1 & Memory CD4 T & A & A\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 3\n",
       "\n",
       "| <!--/--> | seurat_annotations &lt;fct&gt; | donor &lt;fct&gt; | batch &lt;fct&gt; |\n",
       "|---|---|---|---|\n",
       "| sample_37 | Memory CD4 T | B | B |\n",
       "| sample_48 | B            | C | B |\n",
       "| sample_10 | Memory CD4 T | B | A |\n",
       "| sample_2 | CD14+ Mono   | A | A |\n",
       "| sample_51 | NK           | C | B |\n",
       "| sample_1 | Memory CD4 T | A | A |\n",
       "\n"
      ],
      "text/plain": [
       "          seurat_annotations donor batch\n",
       "sample_37 Memory CD4 T       B     B    \n",
       "sample_48 B                  C     B    \n",
       "sample_10 Memory CD4 T       B     A    \n",
       "sample_2  CD14+ Mono         A     A    \n",
       "sample_51 NK                 C     B    \n",
       "sample_1  Memory CD4 T       A     A    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_collapsed <- collapse_counts(pbmc3k@assays$RNA@counts, \n",
    "                                  pbmc3k@meta.data, \n",
    "                                  c('seurat_annotations', 'donor', 'batch'))\n",
    "head(data_collapsed$meta_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BUG: when testing all vs all pairwise, crashes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# table(data_collapsed$meta_data$seurat_annotations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: meta_data should only contain pseudobulk identifying variables\n",
      "Filtered out 10729 genes, analyzing 2985 genes\n",
      "All vars: seurat_annotations, donor, batch\n",
      "Contrast var: seurat_annotations\n",
      "Memory CD4 T vs B\n",
      "Memory CD4 T vs CD14+ Mono\n",
      "Memory CD4 T vs NK\n",
      "Memory CD4 T vs CD8 T\n",
      "Memory CD4 T vs Naive CD4 T\n",
      "Memory CD4 T vs FCGR3A+ Mono\n",
      "Memory CD4 T vs DC\n",
      "Memory CD4 T vs Platelet\n",
      "B vs Memory CD4 T\n",
      "B vs CD14+ Mono\n",
      "B vs NK\n",
      "B vs CD8 T\n",
      "B vs Naive CD4 T\n",
      "B vs FCGR3A+ Mono\n",
      "B vs DC\n",
      "B vs Platelet\n",
      "CD14+ Mono vs Memory CD4 T\n",
      "CD14+ Mono vs B\n",
      "CD14+ Mono vs NK\n",
      "CD14+ Mono vs CD8 T\n",
      "CD14+ Mono vs Naive CD4 T\n",
      "CD14+ Mono vs FCGR3A+ Mono\n",
      "CD14+ Mono vs DC\n",
      "CD14+ Mono vs Platelet\n",
      "NK vs Memory CD4 T\n",
      "NK vs B\n",
      "NK vs CD14+ Mono\n",
      "NK vs CD8 T\n",
      "NK vs Naive CD4 T\n",
      "NK vs FCGR3A+ Mono\n",
      "NK vs DC\n",
      "NK vs Platelet\n",
      "CD8 T vs Memory CD4 T\n",
      "CD8 T vs B\n",
      "CD8 T vs CD14+ Mono\n",
      "CD8 T vs NK\n",
      "CD8 T vs Naive CD4 T\n",
      "CD8 T vs FCGR3A+ Mono\n",
      "CD8 T vs DC\n",
      "CD8 T vs Platelet\n",
      "Naive CD4 T vs Memory CD4 T\n",
      "Naive CD4 T vs B\n",
      "Naive CD4 T vs CD14+ Mono\n",
      "Naive CD4 T vs NK\n",
      "Naive CD4 T vs CD8 T\n",
      "Naive CD4 T vs FCGR3A+ Mono\n",
      "Naive CD4 T vs DC\n",
      "Naive CD4 T vs Platelet\n",
      "FCGR3A+ Mono vs Memory CD4 T\n",
      "FCGR3A+ Mono vs B\n",
      "FCGR3A+ Mono vs CD14+ Mono\n",
      "FCGR3A+ Mono vs NK\n",
      "FCGR3A+ Mono vs CD8 T\n",
      "FCGR3A+ Mono vs Naive CD4 T\n",
      "FCGR3A+ Mono vs DC\n",
      "FCGR3A+ Mono vs Platelet\n",
      "DC vs Memory CD4 T\n",
      "DC vs B\n",
      "DC vs CD14+ Mono\n",
      "DC vs NK\n",
      "DC vs CD8 T\n",
      "DC vs Naive CD4 T\n",
      "DC vs FCGR3A+ Mono\n",
      "DC vs Platelet\n",
      "Platelet vs Memory CD4 T\n",
      "Platelet vs B\n",
      "Platelet vs CD14+ Mono\n",
      "Platelet vs NK\n",
      "Platelet vs CD8 T\n",
      "Platelet vs Naive CD4 T\n",
      "Platelet vs FCGR3A+ Mono\n",
      "Platelet vs DC\n"
     ]
    }
   ],
   "source": [
    "res_pair <- pseudobulk_deseq2(~seurat_annotations + donor + batch, \n",
    "                             data_collapsed$meta_data,\n",
    "                             data_collapsed$counts_mat, verbose = TRUE, mode = 'pairwise')#, vals_test = c('B', 'NK'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "res_min <- summarize_dge_pairs(res_pair, 'min')\n",
    "# res_max <- summarize_dge_pairs(res_pair, 'max')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Compare to other modes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dge <- Reduce(rbind, list(\n",
    "    dplyr::mutate(dge_pairs_min, mode = 'Pairs_min'), \n",
    "    dplyr::mutate(dge_pairs_max, mode = 'Pairs_max'), \n",
    "    dplyr::mutate(dge_1va_col, mode = 'Onevall_collapse'), \n",
    "    dplyr::mutate(dge_1va_no, mode = 'Onevall_no')\n",
    "    )) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt_df <- dge %>% \n",
    "    dplyr::select(feature, log2FoldChange, mode) %>% \n",
    "    spread(mode, log2FoldChange)\n",
    "\n",
    "plt_df <- plt_df[(rowSums(is.na(plt_df)) == 0), ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggforce)\n",
    "fig.size(6, 8)\n",
    "plt_df %>% \n",
    "    ggplot(aes(x = .panel_x, y = .panel_y)) + \n",
    "        geom_point(shape = '.') + \n",
    "        geom_autodensity(alpha = 0.3, position = 'identity') + \n",
    "#         geom_autodensity(position = 'identity') + \n",
    "        facet_matrix(\n",
    "            vars(Pairs_min, Pairs_max, Onevall_collapse, Onevall_no), \n",
    "            layer.diag = 2\n",
    "        ) + \n",
    "        geom_vline(aes(xintercept = 0), linetype = 2) + \n",
    "        geom_hline(aes(yintercept = 0), linetype = 2) + \n",
    "        geom_abline(aes(slope = 1, intercept = 0)) + \n",
    "        NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dge_pairs_min %>% \n",
    "    subset(stat > 0) %>% \n",
    "    dplyr::arrange(-stat) %>% \n",
    "    head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dge_pairs_max %>% \n",
    "    subset(stat > 0) %>% \n",
    "    dplyr::arrange(-stat) %>% \n",
    "    head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test within clusters "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "if (!SeuratData::AvailableData()['ifnb.SeuratData', 'Installed']) {\n",
    "    SeuratData::InstallData(\"ifnb\")\n",
    "}\n",
    "data(\"ifnb\")\n",
    "\n",
    "## randomly assign donors\n",
    "ifnb@meta.data$donor <- factor(sample(LETTERS[1:3], ncol(ifnb), TRUE))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 6</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>orig.ident</th><th scope=col>nCount_RNA</th><th scope=col>nFeature_RNA</th><th scope=col>stim</th><th scope=col>seurat_annotations</th><th scope=col>donor</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>AAACATACATTTCC.1</th><td>IMMUNE_CTRL</td><td>3017</td><td> 877</td><td>CTRL</td><td>CD14 Mono   </td><td>B</td></tr>\n",
       "\t<tr><th scope=row>AAACATACCAGAAA.1</th><td>IMMUNE_CTRL</td><td>2481</td><td> 713</td><td>CTRL</td><td>CD14 Mono   </td><td>C</td></tr>\n",
       "\t<tr><th scope=row>AAACATACCTCGCT.1</th><td>IMMUNE_CTRL</td><td>3420</td><td> 850</td><td>CTRL</td><td>CD14 Mono   </td><td>A</td></tr>\n",
       "\t<tr><th scope=row>AAACATACCTGGTA.1</th><td>IMMUNE_CTRL</td><td>3156</td><td>1109</td><td>CTRL</td><td>pDC         </td><td>B</td></tr>\n",
       "\t<tr><th scope=row>AAACATACGATGAA.1</th><td>IMMUNE_CTRL</td><td>1868</td><td> 634</td><td>CTRL</td><td>CD4 Memory T</td><td>A</td></tr>\n",
       "\t<tr><th scope=row>AAACATACGGCATT.1</th><td>IMMUNE_CTRL</td><td>1581</td><td> 557</td><td>CTRL</td><td>CD14 Mono   </td><td>A</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 6\n",
       "\\begin{tabular}{r|llllll}\n",
       "  & orig.ident & nCount\\_RNA & nFeature\\_RNA & stim & seurat\\_annotations & donor\\\\\n",
       "  & <chr> & <dbl> & <int> & <chr> & <fct> & <fct>\\\\\n",
       "\\hline\n",
       "\tAAACATACATTTCC.1 & IMMUNE\\_CTRL & 3017 &  877 & CTRL & CD14 Mono    & B\\\\\n",
       "\tAAACATACCAGAAA.1 & IMMUNE\\_CTRL & 2481 &  713 & CTRL & CD14 Mono    & C\\\\\n",
       "\tAAACATACCTCGCT.1 & IMMUNE\\_CTRL & 3420 &  850 & CTRL & CD14 Mono    & A\\\\\n",
       "\tAAACATACCTGGTA.1 & IMMUNE\\_CTRL & 3156 & 1109 & CTRL & pDC          & B\\\\\n",
       "\tAAACATACGATGAA.1 & IMMUNE\\_CTRL & 1868 &  634 & CTRL & CD4 Memory T & A\\\\\n",
       "\tAAACATACGGCATT.1 & IMMUNE\\_CTRL & 1581 &  557 & CTRL & CD14 Mono    & A\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 6\n",
       "\n",
       "| <!--/--> | orig.ident &lt;chr&gt; | nCount_RNA &lt;dbl&gt; | nFeature_RNA &lt;int&gt; | stim &lt;chr&gt; | seurat_annotations &lt;fct&gt; | donor &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| AAACATACATTTCC.1 | IMMUNE_CTRL | 3017 |  877 | CTRL | CD14 Mono    | B |\n",
       "| AAACATACCAGAAA.1 | IMMUNE_CTRL | 2481 |  713 | CTRL | CD14 Mono    | C |\n",
       "| AAACATACCTCGCT.1 | IMMUNE_CTRL | 3420 |  850 | CTRL | CD14 Mono    | A |\n",
       "| AAACATACCTGGTA.1 | IMMUNE_CTRL | 3156 | 1109 | CTRL | pDC          | B |\n",
       "| AAACATACGATGAA.1 | IMMUNE_CTRL | 1868 |  634 | CTRL | CD4 Memory T | A |\n",
       "| AAACATACGGCATT.1 | IMMUNE_CTRL | 1581 |  557 | CTRL | CD14 Mono    | A |\n",
       "\n"
      ],
      "text/plain": [
       "                 orig.ident  nCount_RNA nFeature_RNA stim seurat_annotations\n",
       "AAACATACATTTCC.1 IMMUNE_CTRL 3017        877         CTRL CD14 Mono         \n",
       "AAACATACCAGAAA.1 IMMUNE_CTRL 2481        713         CTRL CD14 Mono         \n",
       "AAACATACCTCGCT.1 IMMUNE_CTRL 3420        850         CTRL CD14 Mono         \n",
       "AAACATACCTGGTA.1 IMMUNE_CTRL 3156       1109         CTRL pDC               \n",
       "AAACATACGATGAA.1 IMMUNE_CTRL 1868        634         CTRL CD4 Memory T      \n",
       "AAACATACGGCATT.1 IMMUNE_CTRL 1581        557         CTRL CD14 Mono         \n",
       "                 donor\n",
       "AAACATACATTTCC.1 B    \n",
       "AAACATACCAGAAA.1 C    \n",
       "AAACATACCTCGCT.1 A    \n",
       "AAACATACCTGGTA.1 B    \n",
       "AAACATACGATGAA.1 A    \n",
       "AAACATACGGCATT.1 A    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(ifnb@meta.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>seurat_annotations</th><th scope=col>stim</th><th scope=col>donor</th><th scope=col>N</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>sample_26</th><td>CD14 Mono   </td><td>CTRL</td><td>B</td><td>728</td></tr>\n",
       "\t<tr><th scope=row>sample_52</th><td>CD14 Mono   </td><td>CTRL</td><td>C</td><td>773</td></tr>\n",
       "\t<tr><th scope=row>sample_0</th><td>CD14 Mono   </td><td>CTRL</td><td>A</td><td>714</td></tr>\n",
       "\t<tr><th scope=row>sample_37</th><td>pDC         </td><td>CTRL</td><td>B</td><td> 12</td></tr>\n",
       "\t<tr><th scope=row>sample_2</th><td>CD4 Memory T</td><td>CTRL</td><td>A</td><td>279</td></tr>\n",
       "\t<tr><th scope=row>sample_32</th><td>T activated </td><td>CTRL</td><td>B</td><td>110</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 4\n",
       "\\begin{tabular}{r|llll}\n",
       "  & seurat\\_annotations & stim & donor & N\\\\\n",
       "  & <fct> & <chr> & <fct> & <int>\\\\\n",
       "\\hline\n",
       "\tsample\\_26 & CD14 Mono    & CTRL & B & 728\\\\\n",
       "\tsample\\_52 & CD14 Mono    & CTRL & C & 773\\\\\n",
       "\tsample\\_0 & CD14 Mono    & CTRL & A & 714\\\\\n",
       "\tsample\\_37 & pDC          & CTRL & B &  12\\\\\n",
       "\tsample\\_2 & CD4 Memory T & CTRL & A & 279\\\\\n",
       "\tsample\\_32 & T activated  & CTRL & B & 110\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 4\n",
       "\n",
       "| <!--/--> | seurat_annotations &lt;fct&gt; | stim &lt;chr&gt; | donor &lt;fct&gt; | N &lt;int&gt; |\n",
       "|---|---|---|---|---|\n",
       "| sample_26 | CD14 Mono    | CTRL | B | 728 |\n",
       "| sample_52 | CD14 Mono    | CTRL | C | 773 |\n",
       "| sample_0 | CD14 Mono    | CTRL | A | 714 |\n",
       "| sample_37 | pDC          | CTRL | B |  12 |\n",
       "| sample_2 | CD4 Memory T | CTRL | A | 279 |\n",
       "| sample_32 | T activated  | CTRL | B | 110 |\n",
       "\n"
      ],
      "text/plain": [
       "          seurat_annotations stim donor N  \n",
       "sample_26 CD14 Mono          CTRL B     728\n",
       "sample_52 CD14 Mono          CTRL C     773\n",
       "sample_0  CD14 Mono          CTRL A     714\n",
       "sample_37 pDC                CTRL B      12\n",
       "sample_2  CD4 Memory T       CTRL A     279\n",
       "sample_32 T activated        CTRL B     110"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_collapsed <- collapse_counts(ifnb@assays$RNA@counts, \n",
    "                                  ifnb@meta.data, \n",
    "                                  c('seurat_annotations', 'stim', 'donor'), \n",
    "                                     keep_n = TRUE)\n",
    "head(data_collapsed$meta_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.table: 2 × 14</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>stim</th><th scope=col>CD14 Mono</th><th scope=col>CD4 Naive T</th><th scope=col>CD4 Memory T</th><th scope=col>CD16 Mono</th><th scope=col>B</th><th scope=col>CD8 T</th><th scope=col>T activated</th><th scope=col>NK</th><th scope=col>DC</th><th scope=col>B Activated</th><th scope=col>Mk</th><th scope=col>pDC</th><th scope=col>Eryth</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>CTRL</td><td>2215</td><td> 978</td><td>859</td><td>507</td><td>407</td><td>352</td><td>300</td><td>298</td><td>258</td><td>185</td><td>115</td><td>51</td><td>23</td></tr>\n",
       "\t<tr><td>STIM</td><td>2147</td><td>1526</td><td>903</td><td>537</td><td>571</td><td>462</td><td>333</td><td>321</td><td>214</td><td>203</td><td>121</td><td>81</td><td>32</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 2 × 14\n",
       "\\begin{tabular}{r|llllllllllllll}\n",
       " stim & CD14 Mono & CD4 Naive T & CD4 Memory T & CD16 Mono & B & CD8 T & T activated & NK & DC & B Activated & Mk & pDC & Eryth\\\\\n",
       " <chr> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t CTRL & 2215 &  978 & 859 & 507 & 407 & 352 & 300 & 298 & 258 & 185 & 115 & 51 & 23\\\\\n",
       "\t STIM & 2147 & 1526 & 903 & 537 & 571 & 462 & 333 & 321 & 214 & 203 & 121 & 81 & 32\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 2 × 14\n",
       "\n",
       "| stim &lt;chr&gt; | CD14 Mono &lt;int&gt; | CD4 Naive T &lt;int&gt; | CD4 Memory T &lt;int&gt; | CD16 Mono &lt;int&gt; | B &lt;int&gt; | CD8 T &lt;int&gt; | T activated &lt;int&gt; | NK &lt;int&gt; | DC &lt;int&gt; | B Activated &lt;int&gt; | Mk &lt;int&gt; | pDC &lt;int&gt; | Eryth &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| CTRL | 2215 |  978 | 859 | 507 | 407 | 352 | 300 | 298 | 258 | 185 | 115 | 51 | 23 |\n",
       "| STIM | 2147 | 1526 | 903 | 537 | 571 | 462 | 333 | 321 | 214 | 203 | 121 | 81 | 32 |\n",
       "\n"
      ],
      "text/plain": [
       "  stim CD14 Mono CD4 Naive T CD4 Memory T CD16 Mono B   CD8 T T activated NK \n",
       "1 CTRL 2215       978        859          507       407 352   300         298\n",
       "2 STIM 2147      1526        903          537       571 462   333         321\n",
       "  DC  B Activated Mk  pDC Eryth\n",
       "1 258 185         115 51  23   \n",
       "2 214 203         121 81  32   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.table(data_collapsed$meta_data)[, sum(N), by = .(stim, seurat_annotations)] %>% \n",
    "    tidyr::spread(seurat_annotations, V1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: meta_data should only contain pseudobulk identifying variables\n",
      "Filtered out 7530 genes, analyzing 6523 genes\n",
      "All vars: seurat_annotations, stim\n",
      "Contrast var: seurat_annotations\n",
      "pDC\n",
      "B\n"
     ]
    }
   ],
   "source": [
    "res_mat <- pseudobulk_deseq2(~seurat_annotations + stim, \n",
    "                             data_collapsed$meta_data,\n",
    "                             data_collapsed$counts_mat, \n",
    "                             verbose = TRUE, \n",
    "                             vals_test = c('pDC', 'B'),\n",
    "                             mode = 'within')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Column `group`/`seurat_annotations` joining character vector and factor, coercing into character vector”"
     ]
    },
    {
     "data": {
      "image/png": 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vPmzVOnTo2NjV28eLH5J01OThYIBGPHjr1582Z9fX12dvaHH344ZMiQ6dOnm/Pr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\naJAIAQAAOLT/B1jgLV2Pnc1EAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig.size(2.5, 5)\n",
    "data.table(res_mat)[, sum(padj < .01, na.rm = TRUE) / .N, by = group][order(-V1)] %>% \n",
    "    dplyr::inner_join(\n",
    "        data.table(data_collapsed$meta_data)[, .(ncells = sum(N)), by = seurat_annotations],\n",
    "        by = c('group' = 'seurat_annotations')\n",
    "    ) %>% \n",
    "    ggplot(aes(100 * V1, ncells)) + \n",
    "        geom_point(shape = 21) + \n",
    "        scale_y_log10() + \n",
    "        geom_smooth(method = 'lm', se = FALSE) + \n",
    "        geom_label(aes(label = group), data = . %>% subset(V1 > .2)) + \n",
    "        NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading GitHub repo immunogenomics/presto@master\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R6 (2.4.0 -> 2.4.1) [CRAN]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Skipping 1 packages not available: DESeq2\n",
      "Installing 1 packages: R6\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The downloaded binary packages are in\n",
      "\t/var/folders/cs/n80fh8712qj4njrvf7k11619l6n01t/T//RtmpPPp6JD/downloaded_packages\n",
      "\u001b[32m✔\u001b[39m  \u001b[38;5;247mchecking for file ‘/private/var/folders/cs/n80fh8712qj4njrvf7k11619l6n01t/T/RtmpPPp6JD/remotes922b43ae6bfe/immunogenomics-presto-0f167bf/DESCRIPTION’\u001b[39m\u001b[36m\u001b[36m (537ms)\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mpreparing ‘presto’:\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[32m✔\u001b[39m  \u001b[38;5;247mchecking DESCRIPTION meta-information\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mcleaning src\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mchecking for LF line-endings in source and make files and shell scripts\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mchecking for empty or unneeded directories\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mlooking to see if a ‘data/datalist’ file should be added\u001b[39m\u001b[36m\u001b[39m\n",
      "\u001b[38;5;247m─\u001b[39m\u001b[38;5;247m  \u001b[39m\u001b[38;5;247mbuilding ‘presto_1.0.0.tar.gz’\u001b[39m\u001b[36m\u001b[39m\n",
      "   Warning: invalid uid value replaced by that for user 'nobody'\n",
      "   Warning: invalid gid value replaced by that for user 'nobody'\n",
      "   \n",
      "\r"
     ]
    }
   ],
   "source": [
    "devtools::install_github('immunogenomics/presto')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Updating presto documentation\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing NAMESPACE\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading presto\n",
      "Loading required package: SingleCellExperiment\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing NAMESPACE\n"
     ]
    }
   ],
   "source": [
    "# devtools::document('..')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
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    "\n",
    "\n",
    "\n",
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